Model Taxonomy · Model Landscape

Comprehensive guide to the model landscape as of August 2026, covering model families, capabilities, and selection criteria for production systems.

This chapter provides a comprehensive guide to the model landscape as of August 2026, covering model families, capabilities, and selection criteria for production systems.

Last verified: August 15, 2026. The model landscape evolves rapidly. Always cross-check with provider pricing pages and release notes.

August 2026 headline: Most of the month's releases were post-training refreshes or derivatives rather than new pretraining runs, and no US frontier lab shipped a new flagship base model. The action moved to prices, licenses, and access control. The clear exception is Alibaba's Qwen3.8-Max, a genuinely new 2.4T base whose weights landed August 12. Claude Sonnet 5's introductory $2/$ 10 per 1M became the permanent price on August 10, and the scheduled September 1 rise to $3/$ 15 was canceled, making Sonnet 5 permanently cheaper than the Sonnet 4.6 it replaced. Running the other way, DeepSeek raises V4 prices 3x to 12x effective August 16 at 16:00 UTC, moving to peak and off-peak billing (off-peak is exactly half peak, and peak covers only 01:00-04:00 and 06:00-10:00 UTC). That ends its run as the unambiguous cheap option. OpenAI shipped GPT-5.6-Cyber (August 10, $12.50/$ 75 per 1M) behind a new two-tier Daybreak Blue and Daybreak Red access program, the most concrete production example yet of capability-tiered gating. Google released Gemini 3.7 Flash (August 13) at half price through year-end, and SpaceXAI released Grok 4.6 (August 12) with a 500K context. On open weights the licensing picture split: Alibaba's Qwen3.8-Max (August 12, 2.4T/95B active) shipped under a bespoke commercially gated license while its Qwen3.8-27B sibling (August 14) shipped plain Apache 2.0, Meta returned to open weights with Muse Glimmer (August 10, 30B, Apache 2.0), and Z.ai withheld GLM-5.3's weights pending safety evaluation after cyber capability grew faster than expected. Claude Opus 4.1 retired on August 5, closing out the last $15/$ 75 Opus tier. Benchmark figures throughout this section are largely vendor-reported; confirm on independent leaderboards.

July 2026 headline: Anthropic shipped a full generation refresh: Claude Sonnet 5 (June 30, claude-sonnet-5, new default everywhere, introductory $2/$ 10 per 1M through August 31 then $3/$ 15) and Claude Opus 5 (July 24, claude-opus-5, unchanged $5/$ 25 with an optional Fast mode at $10/$ 50 about 2.5x faster). Claude Fable 5 was restored globally July 1 after the export-control suspension, with a new jailbreak-specific cybersecurity classifier; Mythos 5 returned only to roughly 100 US critical-infrastructure organizations via Project Glasswing. GPT-5.6 (Sol, Terra, Luna) reached general availability July 9, and on July 30 OpenAI cut Luna 80% to $0.20/$ 1.20 and Terra 20% to $2/$ 12 (Sol stays $5/$ 30). The open-weight frontier had its strongest month ever: Moonshot Kimi K3 (July 16, weights July 27) is the largest open-weight model to date at 2.8T total / 104B active with a 1M context, and Thinking Machines Lab debuted Inkling (July 15, 975B / 41B active, open weights), the leading US open-weights model. Google shipped Gemini 3.6 Flash, 3.5 Flash-Lite, and a government-gated 3.5 Flash Cyber (July 21) while delaying Gemini 3.5 Pro. Meta Muse Spark 1.1 (July 9) arrived with Meta's first paid self-serve model API ( $1.25/$ 4.25 per 1M). Black Forest Labs announced FLUX 3 (July 23), a unified image, video, audio, and action model, in gated early access. Benchmark figures across these launches are largely vendor-reported; confirm on independent leaderboards.

June 2026 headline: Anthropic released Claude Fable 5 (June 9, claude-fable-5, $10/$ 50 per 1M, 1M context), its most capable widely released model: a Mythos-class model made safe for general availability, with an Opus 4.8 fallback safeguard on sensitive topics. Claude Mythos 5 ships the same day as the unrestricted variant for Project Glasswing partners, succeeding Mythos Preview at less than half its price.

June 10-26 update: A dense second wave of June launches followed. Google DeepMind DiffusionGemma (June 10, Apache 2.0) is Google DeepMind's first open-weight text-diffusion model: a 26B Mixture-of-Experts (~4B active) that denoises blocks of tokens in parallel for roughly 4x faster generation on a single H100, trading some quality versus standard Gemma 4. Gemini 3.5 Live Translate (June 9, built on Gemini 3 Pro) added real-time speech-to-speech translation across 70+ languages in public preview via the Gemini Live API and AI Studio. Cohere North Mini Code 1.0 (June 9, Apache 2.0) is Cohere's first open coding model, a 30B / 3B-active MoE that runs on one H100. Moonshot Kimi K2.7 Code (June 12, Modified MIT) tunes K2.6 for long-horizon software work (1T / 32B-active MoE, roughly 30% fewer thinking tokens). Z.ai GLM-5.2 (coding-plan access June 13, open weights under MIT June 16-17) is a 744B / 40B-active MoE with a 1M context that reports SWE-Bench Pro 62.1, ahead of GPT-5.5 on that benchmark, at roughly $1.40 /$ 4.40 per 1M. xAI Grok Imagine Video 1.5 reached general availability June 16 (image-to-video with synchronized audio, $0.080 per second of video), and **Grok 4.3** arrived on Amazon Bedrock June 15 ($ 1.25 / $2.50 per 1M, xAI's first model there). Alibaba's official Qwen Cloud changelog lists a June snapshot adding vision to Qwen 3.7-Max (text-only at its May launch), though some independent coverage attributes that vision update to Qwen 3.7-Plus instead, so verify before relying on it. Separately, on June 12 Anthropic suspended access to Claude Fable 5 and Claude Mythos 5 following a US export-control directive, with Mythos 5 later cleared for a limited set of US institutions. Then on June 26, OpenAI previewed GPT-5.6 (Sol, Terra, and Luna), its next-generation line, in a limited release to a small set of US-government-approved partners over dual-use cybersecurity concerns, echoing the Anthropic restriction; Sol claims a new Terminal-Bench 2.1 record and Terra targets GPT-5.5-level quality at about half the cost. Coding scores here are largely vendor-reported; confirm on independent leaderboards.

May 2026 recap: Anthropic Claude Opus 4.8 (May 28, same $5/$ 25 price as Opus 4.7; Dynamic Workflows research preview with hundreds of parallel subagents; fast mode at $10/$ 50 is 3x cheaper than the Opus 4.7 fast mode); OpenAI GPT-5.5 (April 23) and GPT-5.5 Instant (May 5, default in ChatGPT); Claude Opus 4.7 (April 16, GA on Bedrock/Vertex/Foundry); Google Gemma 4 (April 2, Apache 2.0) and Gemini 3.2 Flash (quiet rollout May 5); DeepSeek V4 Pro and V4 Flash (April 24; 75% V4 Pro discount made permanent May 22, new list price $0.435/$ 0.87 per 1M from June 1); Moonshot Kimi K2.6 (April 20, 1T MoE / 32B active); Alibaba Qwen 3.6 Plus / 3.6-35B-A3B / 3.6 Max-Preview; Mistral Medium 3.5 (April 29, unified chat/reasoning/coding/vision); Meta Muse Spark (April 8, first closed-weight Meta model); Llama 4 Behemoth release paused through fall 2026 amid capability concerns. SWE-bench Verified published leaders before the Fable 5 launch: Claude Mythos Preview 93.9%, GPT-5.5 88.7%, Claude Opus 4.8 88.6%; ARC-AGI-2 leader: GPT-5.5 at 85.0%. Anthropic describes Fable 5 as state of the art on nearly all tested benchmarks; standard numeric scores were not in the launch post, so verify on the leaderboards.

Model Categories
Frontier Models (May 2026)
Reasoning Models
Open Source Models
Specialized Models
Embedding Models
Model Selection Framework & Semantic Routing
Sovereign AI & Data Residency
Capability Comparison
Interview Questions
References

Model Categories

By Capability Level (April 2026 Reality)

Tier	Characteristics	Examples	Use Case
Frontier	State-of-the-art reasoning, agentic mastery	Claude Fable 5, Claude Opus 4.8, GPT-5.5, Gemini 3.1 Pro, Grok 4.3	Complex reasoning, coding, production agents
Fast/Efficient	Sub-200ms, cost-optimized	Gemini 3.1 Flash, GPT-5.5-mini, Claude Haiku 4.5, DeepSeek V4 Flash	High-volume streaming, UI, real-time
Battle-Tested	Mature, widely-deployed, stable	Claude Sonnet 4.6, GPT-5.5 Instant, Gemini 3.1 Pro	Enterprise production workloads
Small/Edge	Private, edge, specialized	Llama 4 Scout, Mistral Small 4, Phi-4	Local privacy, on-device, MoE-efficient
Reasoning-Heavy	Extended internal CoT	Claude Opus 4.8 (thinking), GPT-5.5 reasoning, Gemini 3.1 Pro Deep Think, DeepSeek-R1	Math, code debug, multi-step logic

By Reasoning Mode (2025–2026)

Mode	Capability	Models	Use Case
Standard	Fast, intuitive response	GPT-5.5-mini, Claude Sonnet 4.6	Chat, simple extraction
Extended Thinking	Internal scratchpad CoT before output	Claude Opus 4.8, GPT-5.5 reasoning, DeepSeek-R1	Math, code debugging, planning
Hybrid	User-controllable reasoning depth	Claude Opus 4.8, GPT-5.5	Variable complexity tasks

Frontier Models (June 2026)

Claude Opus 5 (Anthropic) - July 2026 NEW

Attribute	Value
Model ID	`claude-opus-5`
Context Window	1M tokens (default and max; 128K max output)
Input / Output Cost	$5.00 /$ 25.00 per 1M (unchanged from Opus 4.8)
Fast mode	$10.00 /$ 50.00 per 1M, about 2.5x faster
Benchmarks	Anthropic's launch post, reporting the pre-release benchmark it called Frontier-Bench v0.1 (since renamed Terminal-Bench 3.0): 43.3% at max effort vs GPT-5.6 Sol's 34.4%, Fable 5's 33.7%, and Opus 4.8's 18.7%. Within 0.5% of Fable 5 on CursorBench 3.2 at about half the cost per task; roughly 3x the next-best model on ARC-AGI 3. Vendor-reported.
Released	July 24, 2026 (Claude API, Claude Code, Claude Cowork; new default on Claude Max)

What it is: The Opus line's generational successor at unchanged pricing, aimed at long-horizon agentic coding and computer use. Beta features include mid-conversation tool changes and automatic fallback routing. The dual-price Fast mode continues the pattern Opus 4.8 introduced: one model, two latency tiers.

Best for: Agentic coding and computer-use workloads where Fable 5's ceiling is not needed; the price-performance flagship of the Claude line as of late July 2026.

Claude Sonnet 5 (Anthropic) - July 2026 NEW

Attribute	Value
Model ID	`claude-sonnet-5`
Context Window	1M tokens per third-party coverage (not stated in the launch post)
Input / Output Cost	$2.00 /$ 10.00 per 1M (permanent since August 10, 2026)
Cache / Batch	Cache write $2.50 per 1M (5 min) or$ 4.00 (1 hr); cache hit $0.20; Batch API$ 1.00 / $5.00
Positioning	The most agentic Sonnet yet: planning, browser and terminal tool use, autonomous operation approaching Opus 4.8 at lower cost
Safety posture	Cyber safeguards on by default; deliberately reduced cybersecurity capability relative to Opus-class models
Released	June 30, 2026 (default model across consumer and developer products same day)

What it is: The new production workhorse, replacing Sonnet 4.6 as the default. On August 10, 2026 Anthropic made the introductory $2/$ 10 rate permanent and canceled the September 1 increase to $3/$ 15, so Sonnet 5 is permanently cheaper than the Sonnet 4.6 it succeeds (still $3/$ 15). Cost models built on the reversion assumption should be revised down.

Best for: Production agent fleets, coding at scale, and the default tier in cost-aware routing stacks.

Claude Fable 5 (Anthropic) - June 2026 NEW

Attribute	Value
Model ID	`claude-fable-5`
Context Window	1M tokens (Opus 4.7 tokenizer; roughly 30% more tokens than pre-4.7 models for the same text)
Max Output	128K tokens
Input Cost	$10.00 / 1M tokens
Output Cost	$50.00 / 1M tokens
Thinking	Adaptive thinking, always on (no separate extended-thinking toggle)
Multimodal	Text + Vision (new state of the art on vision tasks per Anthropic)
Benchmarks	State of the art on nearly all tested benchmarks per Anthropic; highest frontier score on Cognition's FrontierCode, highest on the Hebbia Finance Benchmark, ViBench, and CursorBench. Standard numeric scores (SWE-bench, GPQA) were not published in the launch post.
Released	June 9, 2026 (GA on Claude API, Claude Platform on AWS, Amazon Bedrock, Vertex AI, Microsoft Foundry)

What it is: A Mythos-class model made safe for general availability. Until now the Mythos line (SWE-bench Verified 93.9% on Mythos Preview) was restricted to ~11 Project Glasswing partners over dual-use cybersecurity concerns. Fable 5 brings that capability tier to everyone by pairing it with conservative safeguards.

The Opus 4.8 fallback safeguard: When Fable 5's classifiers detect a request in one of three categories (offensive cyber techniques, bioweapon-adjacent biology and chemistry, or attempts to distill the model), the response is silently delegated to Claude Opus 4.8 and the user is informed. Anthropic says this triggers in under 5% of sessions and is deliberately tuned conservative, so some harmless requests get caught. Architecturally this is a production example of model-tier routing as a safety control, not just a cost control.

Best for: The most demanding reasoning, long-horizon agentic work, vision-heavy tasks, and workloads where capability ceiling matters more than unit cost. Anthropic reports it sustains autonomous operation longer than any previous Claude model.

Considerations: 2x the per-token price of Opus 4.8 ( $10/$ 50 vs $5/$ 25), so route only ceiling-bound work to it. Mythos-class traffic carries a 30-day data retention requirement (not used for training; access-logged; deleted after 30 days in almost all cases), which matters for compliance reviews. On subscription plans it was included at no extra cost June 9-22, then moved to usage credits. There is no Fable-tier fast mode or published cache/batch discount at launch; check the pricing page.

Claude Mythos 5 (Anthropic) - RESTRICTED ACCESS

Attribute	Value
Model ID	`claude-mythos-5`
Status	Limited availability: Project Glasswing partners and select biology researchers
Relationship	Same underlying model as Fable 5 with safeguards lifted in some areas
Pricing	$10 /$ 50 per 1M (less than half of Mythos Preview)
Released	June 9, 2026

Why it matters: Succeeds Claude Mythos Preview at comparable or somewhat stronger capability and much lower price. The Fable/Mythos split formalizes a two-track release pattern: one safeguarded general release, one unrestricted release for vetted defenders.

Claude Opus 4.8 (Anthropic) - May 2026

Attribute	Value
Context Window	1M tokens (standard pricing across the full window)
Input Cost	$5.00 / 1M tokens (same as 4.7)
Output Cost	$25.00 / 1M tokens (same as 4.7)
Cache: 5m write	$6.25 / 1M tokens
Cache: 1h write	$10.00 / 1M tokens
Cache: hit / refresh	$0.50 / 1M tokens
Batch API	$2.50 /$ 12.50 per 1M (50% discount)
Fast mode (research preview)	$10 /$ 50 per 1M (about 2.5x faster; 3x cheaper than the Opus 4.7 fast mode which was $30 /$ 150)
Extended Thinking	Native, adaptive mode
Multimodal	Text + Higher-resolution Vision
SWE-bench Verified	88.6%
SWE-Bench Pro	69.2% (up from 64.3% on Opus 4.7)
Terminal-Bench 2.1	74.6% (GPT-5.5 still leads at 78.2%)
GDPval-AA	1890 Elo (up from 1753 on Opus 4.7)
OSWorld-Verified	82.3%
Online-Mind2Web	84%
Released	May 28, 2026 (GA on Claude API, AWS Bedrock, Vertex AI)

Best for: Long-running autonomous coding work in Claude Code, codebase-scale migrations, agentic workflows that need parallel subagents, and workloads where the alignment and honesty gains matter.

Key features over Opus 4.7:

Dynamic Workflows (research preview): Claude plans the work and runs hundreds of parallel subagents in a single Claude Code session, verifies their outputs, and reports back. Suited for codebase-scale migrations across hundreds of thousands of lines.
Mid-task system messages: The Messages API now accepts system messages mid-conversation, useful for steering long agent runs without ending the session.
Optional fast mode at roughly 2.5x speed for $10 /$ 50 per 1M, priced 3x lower than the Opus 4.7 fast mode.
Effort-control toggle in claude.ai and Cowork lets users tune reasoning depth per turn.
Expanded Claude Code rate limits.

Considerations: Tokenizer is the same one introduced in Opus 4.7 (up to 35% more tokens than the pre-4.7 tokenizer for the same fixed text). GPT-5.5 still holds the SWE-Bench Verified leaderboard at 88.7% and leads Terminal-Bench 2.1 at 78.2%. GPQA Diamond slipped 0.6 pts versus Opus 4.7. Anthropic's tokenizer change means token counts and bills for the same text are not directly comparable to pre-4.7 models. There was no Claude Sonnet 4.8; the line jumped to Claude Sonnet 5 on June 30, 2026, which replaced Sonnet 4.6 as the production workhorse.

NOTE
Retired August 5, 2026: claude-opus-4-1-20250805 was removed from the Claude API, closing out the last $15/$ 75 per 1M Opus tier. Every first-party Anthropic Opus SKU is now $5/$ 25 (or $10/$ 50 in Fast mode). The model remains available on Amazon Bedrock and Google Cloud, which set their own retirement schedules, so code pinned to that ID fails on the first-party API while still working on the partner clouds.

Claude Opus 4.7 (Anthropic)

Attribute	Value
Context Window	1M tokens
Max Output	128K tokens
Input Cost	$5.00 / 1M tokens (same as 4.6)
Output Cost	$25.00 / 1M tokens (same as 4.6)
Extended Thinking	Native, Adaptive mode
Multimodal	Text + Higher-resolution Vision
SWE-bench Verified (Adaptive)	87.6% (May 13, 2026)
Released	April 16, 2026 (GA on API, Bedrock, Vertex, Microsoft Foundry)

Best for: Autonomous coding agents (powers Claude Code), multi-file refactors, complex reasoning. Same pricing as 4.6 - straight upgrade for most workloads. Considerations: Use Sonnet 4.6 for cost-sensitive workloads; Opus 4.7 mainly for tasks requiring peak coding/agentic quality.

Claude Mythos Preview (Anthropic) - SUCCEEDED BY MYTHOS 5

Attribute	Value
Status	Restricted research preview, Project Glasswing partners only (~11 orgs: AWS, Apple, Cisco, Google, Microsoft, NVIDIA, Palo Alto, etc.)
Reason for restriction	Dual-use cybersecurity capabilities
SWE-bench Verified	93.9% (May 13, 2026; the published SOTA before the Fable 5 / Mythos 5 launch)
Released	April 7, 2026 (restricted partner preview); succeeded by Claude Mythos 5 on June 9, 2026 at less than half the price

Best for: Historical reference. Its capability tier reached general availability as Claude Fable 5 on June 9, 2026; new Glasswing work should target Mythos 5.

Claude Opus 4.6 (Anthropic)

Attribute	Value
Context Window	1M tokens
Max Output	128K tokens
Input Cost	$5.00 / 1M tokens
Output Cost	$25.00 / 1M tokens
Extended Thinking	Native adaptive thinking (configurable budget_tokens)
Multimodal	Text + Vision
Highlights	Most capable Anthropic model; exceptional coding and reasoning
Released	February 2026

Best for: Most complex reasoning, autonomous software engineering, agentic workflows. Considerations: Premium pricing; use Sonnet 4.6 for tasks that don't need peak capability.

Claude Sonnet 4.6 (Anthropic)

Attribute	Value
Context Window	1M tokens
Input Cost	$3.00 / 1M tokens
Output Cost	$15.00 / 1M tokens
Extended Thinking	Supported
Multimodal	Text + Vision
Highlights	Handles tasks previously requiring Opus tier; best cost/quality balance
Released	February 2026

Best for: Production coding agents (powers Claude Code), complex reasoning at scale. Considerations: Now covers most Opus-level tasks at lower cost. Strong default for most workloads.

GPT-5.4 (OpenAI)

Attribute	Value
Context Window	272K tokens (standard); extended available
Input Cost	$2.50 / 1M tokens
Output Cost	$15.00 / 1M tokens
Multimodal	Text, Vision, native computer use
Highlights	Built-in computer-use capabilities; 33% fewer factual errors vs GPT-5.2; combines coding + agentic strengths
Released	March 2026

Best for: Agentic workflows with computer use, coding, professional tasks. Considerations: Long-context pricing doubles at 272K+ tokens.

GPT-5.4-mini (OpenAI)

Attribute	Value
Context Window	272K tokens
Input Cost	$0.75 / 1M tokens
Output Cost	$4.50 / 1M tokens
Highlights	Best cost/performance for high-volume GPT-5 tier workloads
Released	March 2026

Best for: High-volume API calls, cost-optimized reasoning, production chatbots.

GPT-5.4 Pro (OpenAI)

Attribute	Value
Context Window	272K tokens
Input Cost	$30.00 / 1M tokens
Output Cost	$180.00 / 1M tokens
Highlights	Maximum reasoning power; premium tier for hardest tasks
Released	March 2026

Best for: Competition-level math, complex multi-step reasoning. Considerations: Very expensive; use standard GPT-5.4 or mini for volume.

GPT-5.6 Sol / Terra / Luna (OpenAI) - GA July 9, 2026

Attribute	Value
Variants	Sol (flagship), Terra (balanced), Luna (fast, low cost)
Context Window	1M tokens (all three); 128K max output; knowledge cutoff February 16, 2026
Sol pricing	$5.00 /$ 30.00 per 1M
Terra pricing	$2.00 /$ 12.00 per 1M (cut 20% from $2.50/$ 15 on July 30)
Luna pricing	$0.20 /$ 1.20 per 1M (cut 80% from $1/$ 6 on July 30)
Reasoning	"max" reasoning effort plus an "ultra" mode that uses subagents to accelerate complex work
API features at GA	Programmatic tool calling, multi-agent support, explicit prompt-cache breakpoints
Benchmarks	Sol: 53.6 on Agents' Last Exam (13.1 points ahead of Claude Fable 5) and a Terminal-Bench 2.1 record. Claude Fable 5 still leads SWE-Bench Pro (80 vs Sol's 64.6), a benchmark OpenAI publicly disputes. Vendor-reported.
Released	Limited preview June 26, 2026; general availability July 9, 2026

What it is: OpenAI's next-generation flagship line, shipped for the first time as three models. The June 26 preview was gated at the request of the US government over dual-use cybersecurity capability; GA followed a 13-day review. The three-tier structure plus the steep July 30 cuts (Luna at $0.20/$ 1.20 is priced against open-weight competition) reset the routing math for anyone doing tiered model selection.

Best for: Sol for frontier agentic work and cybersecurity-adjacent coding; Terra as the GPT-5.5-class production default at roughly half GPT-5.5's price; Luna for high-volume classification, extraction, and routing tiers.

GPT-5.6-Cyber (OpenAI) - August 2026 NEW (restricted)

Attribute	Value
Model ID	`gpt-5.6-cyber`
Context Window	400K total (272K max input, 128K max output)
Input / Output Cost	$12.50 /$ 75.00 per 1M; cached input $1.25
Access	Daybreak Red tier only, with identity verification, legal attestations, and approved use cases. Responses API only. Hardware security keys become mandatory on individual Daybreak accounts from September 1, 2026
Refusal posture	Trained for a lower refusal rate on dual-use security work: 95.0% completion on OpenAI's internal Advanced Cybersecurity Completion Rate eval versus 1.5% for GPT-5.6 Sol
Released	August 10, 2026 (the Daybreak Blue and Red tier split appears in the API changelog dated August 7)

What it is: A cybersecurity model built on GPT-5.6 Sol, shipped alongside a split of the Daybreak program into two tiers. Daybreak Blue gives approved defenders access to general-purpose frontier models for vulnerability discovery, secure code review, detection engineering, and incident response. Daybreak Red is separately approved and gates gpt-5.6-cyber for vulnerability reproduction, exploit validation, penetration testing, and red teaming.

Why it matters architecturally: This is the clearest production instance of capability-tiered gating to date. A model that is deliberately more permissive than the frontier default, priced at 2.5x Sol, restricted to a single API surface, and fenced behind identity verification plus mandatory hardware 2FA is a reference design for how labs are operationalizing dual-use access. Compare with Anthropic's Fable 5 and Mythos 5 split and Google's Gemini 3.5 Flash Cyber: three labs, three variations on the same tiering pattern.

GPT-5.5 (OpenAI) - May 2026 NEW

Attribute	Value
Context Window	1M tokens
Input Cost	$5.00 / 1M tokens
Output Cost	$30.00 / 1M tokens
Multimodal	Text, Image, Audio, Video
ARC-AGI-2	85.0% (May 13, 2026 - leader)
Released	April 23, 2026

Best for: Highest-quality multimodal workloads; current ARC-AGI-2 leader. Pitched as "new class of intelligence for real work" - replaces GPT-5.4 for top-tier reasoning + multimodal. Considerations: ~2× the input cost of GPT-5.4 ( $2.50 →$ 5.00) and ~2× output ( $15 →$ 30). Use GPT-5.5 Instant for chat workloads where the price isn't justified.

GPT-5.5 Instant (OpenAI) - May 2026 NEW

Attribute	Value
Status	Default in ChatGPT and `chat-latest` in API since May 5, 2026
Hallucination Reduction	52.5% fewer on high-stakes prompts (medicine/law/finance) vs GPT-5.3 Instant
AIME 2025	81.2% (up from 65.4% on GPT-5.3 Instant)
Response Length	~30% fewer words/lines than predecessor
Released	May 5, 2026

Best for: Default ChatGPT-equivalent workloads, instant chat, high-stakes domains where hallucination reduction matters. Considerations: Replaces GPT-5.3 Instant as the chat default. GPT-5.2-chat-latest and GPT-5.3-chat-latest deprecated May 8, 2026.

GPT-Realtime-2, Translate, Whisper (OpenAI) - May 2026 NEW

Attribute	Value
Capability	Realtime voice with GPT-5-class reasoning
Translate Coverage	70+ input → 13 output languages
Pricing	$32 /$ 64 per 1M audio tokens (input/output)
Released	May 7, 2026

Best for: Real-time voice agents, multilingual translation, voice-first products. Realtime API Beta was removed May 12, 2026 - Realtime-2 is the supported path.

Gemini 3.1 Pro (Google)

Attribute	Value
Context Window	1M tokens
Input Cost	$2.00 / 1M tokens (standard);$ 4.00 (200K+)
Output Cost	$12.00 / 1M tokens (standard);$ 18.00 (200K+)
Multimodal	Native: Text, Vision, Audio, Video
Highlights	State-of-the-art Google reasoning; powerful agentic and coding capabilities
Released	February 2026

Best for: Complex reasoning, multimodal analysis, long-context workloads. Considerations: Replaced Gemini 3 Pro Preview. Gemini 2.5 Pro/Flash deprecated June 2026.

Gemini 3.1 Flash (Google)

Attribute	Value
Context Window	1M tokens
Input Cost	$0.10 / 1M tokens
Output Cost	$3.00 / 1M tokens
Multimodal	Native: Text, Vision, Audio, Video
Highlights	Fastest Google model; best price/performance for high-volume
Released	March 2026

Best for: Real-time multimodal apps, high-volume pipelines, long-context RAG.

Gemini 3.2 Flash (Google) - May 2026 NEW

Attribute	Value
Status	Quiet rollout in iOS Gemini app and Google AI Studio May 5, 2026 (no formal announcement yet)
Released	May 5, 2026

Best for: Likely successor to 3.1 Flash for high-volume workloads. Treat as preview - pricing and full capability disclosure pending official launch.

Gemini Deep Research / Deep Research Max (Google) - May 2026 NEW

Attribute	Value
Built on	Gemini 3.1 Pro
Capabilities	MCP support; native chart/infographic generation; extended test-time compute; async background workflows
Released	April 21, 2026

Best for: Research agents, document synthesis, long-running async workflows. The MCP support makes it the first Google research-agent product with first-class tool integration.

Gemini Robotics-ER 1.6 (Google DeepMind) - May 2026 NEW

Attribute	Value
Domain	Physical robotics, embodied reasoning
New capability	Reading gauges/sight glasses
Deployment	Boston Dynamics Spot
Released	April 14, 2026

Best for: Robotics applications requiring vision-language grounding for physical actions. Available via Gemini API and AI Studio.

Gemini 3.7 Flash (Google) - August 2026 NEW

Attribute	Value
Model ID	`gemini-3.7-flash`
Context Window	1,048,576 tokens in / 65,536 out
Input / Output Cost	$0.75 /$ 3.75 per 1M through December 31, 2026, then $1.50 /$ 7.50. Context caching $0.075 per 1M; Batch$ 0.375 / $1.875
Multimodal	Text, image, audio, video; first Gemini model with agentic video processing on by default
Knowledge cutoff	March 2026
Released	August 13, 2026 (GA)

What it is: Google's workhorse tier, built on Gemini 3.6 Flash with what the model card describes as algorithmic improvements to the reasoning foundation rather than a new pretraining run. Customizable thinking configurations trade quality against cost and latency per request. Google-reported gains over 3.6 Flash include FrontierCode 1.1 Main 43.6% versus 34.4% and WebDev Arena Elo 1588 versus 1538.

Considerations: The half-price introductory rate expires December 31, 2026 and then doubles, so run cost models against the January 2027 numbers before committing to volume. Gemini 3.5 Pro still has not shipped as of mid-August; gemini-3.1-pro-preview remains Google's top Pro-tier entry.

Grok 4.6 (SpaceXAI) - August 2026 NEW

Attribute	Value
Model ID	`grok-4.6`
Context Window	500K tokens
Input / Output Cost	$2.00 /$ 6.00 per 1M below a 200K prompt; $4.00 /$ 12.00 at or above 200K. Cached input $0.50
Reasoning	Effort settings low, medium, high (default), xhigh
Knowledge cutoff	February 1, 2026
Released	August 12, 2026

What it is: SpaceXAI's frontier model, focused on long-running agents and interactive visual work. Artificial Analysis Intelligence Index 61, up from 56 for Grok 4.5 High.

Two traps worth knowing. The higher long-prompt rate applies to all tokens in the request once the prompt reaches 200K, not just the tokens past the threshold. And cached input got more expensive than Grok 4.5 ( $0.50 versus$ 0.30 per 1M), so cache-heavy agent loops do not automatically get cheaper on the upgrade. Note the vendor name: xAI completed a rebrand to SpaceXAI, so current docs and release notes use the new name.

Grok 4 (xAI)

Attribute	Value
Context Window	256K tokens
Input Cost	$3.00 / 1M tokens
Output Cost	$15.00 / 1M tokens
Highlights	Native tool use and real-time search; competitive reasoning
Released	July 2025 (Grok 4.20 beta: February 2026)

Best for: Live web research, reasoning-heavy tasks, real-time X/web integration. Considerations: Grok 4.1 Fast available at $0.20/$ 0.50 for high-volume.

Model Comparison: Frontier Tier (June 2026)

Model	Reasoning	Coding	Context	Agentic	Cost
Claude Fable 5	★★★★★	★★★★★	★★★★★	★★★★★	$$$
Claude Mythos 5 (restricted)	★★★★★	★★★★★	★★★★★	★★★★★	$$$
Claude Opus 4.8	★★★★★	★★★★★	★★★★★	★★★★★	$$
Claude Opus 4.7	★★★★★	★★★★★	★★★★★	★★★★★	$$
GPT-5.5	★★★★★	★★★★★	★★★★★	★★★★★	$$
Claude Opus 4.6	★★★★★	★★★★★	★★★★★	★★★★★	$$
GPT-5.4	★★★★★	★★★★★	★★★★	★★★★★	$$
Claude Sonnet 4.6	★★★★★	★★★★★	★★★★★	★★★★★	$$
Gemini 3.1 Pro	★★★★★	★★★★	★★★★★	★★★★	$
Grok 4	★★★★	★★★★	★★★★	★★★★	$$
GPT-5.4-mini	★★★★	★★★★	★★★★	★★★	$
Gemini 3.1 Flash	★★★	★★★	★★★★★	★★★	$
GPT-5.5 Instant	★★★★	★★★★	★★★★	★★★★	$

Production Heritage & Maturity

While frontier models lead on benchmarks, many enterprise systems rely on battle-tested models:

Model Family	Production Since	Maturity Note
GPT-4o	May 2024	Most mature ecosystem; lowest latency variance; highest rate limits.
Claude 3.5 Sonnet / 3.7 Sonnet	June 2024	Gold standard for tool-use reliability and structured output.
Gemini 2.5 Pro	March 2025	Proven at scale; stable long-context. Being deprecated June 2026 in favor of 3.x.
o1 / o3	Sept 2024	Well-understood reasoning model failure modes; o3 superseded o1.

Why stay on "older" frontier models?

Consistency: New models have "release-window" latency spikes and behavior shifts.
Cost Efficiency: Previous generation is often 50-80% cheaper after a new release.
Guardrail Tuning: Security and moderation layers are more refined.

Open Source Models

Llama 4 Family (Meta) -- NEW April 2026

Model	Parameters	Context	Architecture	Notes
Llama 4 Scout	17B active / 16 experts (MoE)	10M	Sparse MoE	Industry-leading 10M context; fits single H100; beats Gemma 3, Gemini 2.0 Flash-Lite
Llama 4 Maverick	17B active / 128 experts (MoE)	1M	Sparse MoE	Beats GPT-4o and Gemini 2.0 Flash; comparable to DeepSeek V3 at half active params
Llama 4 Behemoth	~288B active (est.)	-	Dense MoE	Still training; outperforms GPT-4.5, Gemini 2.0 Pro on STEM benchmarks

Strengths:

First Llama generation with Mixture-of-Experts architecture
Natively multimodal from the ground up (text, image, video input)
Open weights on Hugging Face; available via Meta AI on WhatsApp, Messenger, Instagram
Scout's 10M token context window is industry-leading for open models

Llama 3.x Family (Meta) -- Previous Generation

Model	Parameters	Context	License	Notes
Llama 3.3 70B	70B	128K	Llama 3.3	Still widely deployed; strong general model
Llama 3.1 405B	405B	128K	Llama 3.1	Largest dense Meta model; being superseded by Llama 4

Note: Llama 3.x remains widely used in production, but Llama 4 Scout/Maverick offer superior performance with lower active parameter counts thanks to MoE.

DeepSeek Family

Model	Parameters	Context	Status	Notes
DeepSeek V4 Pro	1.6T total / 49B active (MoE)	1M	GA	Previewed April 24, 2026. Uses ~27% compute / 10% memory of V3.2 at 1M tokens. SWE-bench Verified 80.6%. NIST CAISI evaluation (May 2026) places it ~8 months behind US frontier (Elo ~800). Open weights on Hugging Face. API: $0.435 /$ 0.87 per 1M input/output (75% discount made permanent May 22, 2026, effective June 1). Cache-hit input $0.003625/M.
DeepSeek V4 Flash	284B total / 13B active (MoE)	1M	GA	Smaller-active variant for high-throughput workloads. API: $0.14 /$ 0.28 per 1M (cache-hit $0.0028/M). Cheapest frontier-class 1M-context API as of May 2026.
DeepSeek-V3.2	671B (MoE)	128K	Frontier	General-purpose; 98% cache-hit discount ( $0.28/$ 0.42 per 1M base). Largely superseded by V4 Flash for new builds.
DeepSeek-V3	671B (MoE, 37B active)	128K	Frontier	GPT-4o level at a fraction of training cost; open weights.
DeepSeek-R1	671B (MoE)	128K	Reasoning	Matches o1 on math/code; first open-source reasoning model.
DeepSeek-R1-Distill	7B–70B	-	Reasoning	Distilled to smaller models; cost-efficient reasoning.

Key May 2026 context: DeepSeek V4 Pro (released April 24, with the 75% promotional discount made permanent on May 22) closed the gap with US frontier models on multiple benchmarks at a fraction of the cost. At $0.435 /$ 0.87 per 1M, V4 Pro is roughly 10x cheaper than Claude Opus 4.7 ( $5 /$ 25) and 5-10x cheaper than GPT-5.5 ( $5 /$ 30) for comparable tasks. V4 Flash drops the floor further to $0.14 /$ 0.28 per 1M with the same 1M context window. The 98% cache-hit discount on both makes V4 the dominant choice for high-volume RAG and classification workloads where prompts are cache-friendly. DeepSeek R2 (reasoning successor to R1) remains delayed per reports about Huawei Ascend training challenges.

Moonshot Kimi Family - May 2026 NEW

Model	Parameters	Context	Notes
Kimi K3	2.8T total / 104B active (MoE)	1M	July 16, 2026 NEW (open weights July 27). Largest open-weight model to date. Always-on thinking, multimodal. $3 /$ 15 per 1M ($0.30 cached input). Artificial Analysis Intelligence Index 57.1, third overall at launch behind Fable 5 and GPT-5.6 Sol; first open model to top WebDev Arena. Moonshot's flagship, superseding K2.7 Code.
Kimi K2.6	1T total / 32B active (MoE)	-	Released April 20, 2026. Modified MIT license. Native video input; Agent Swarm scaling to 300 sub-agents and 4,000 coordinated steps. Ties GPT-5.5 on SWE-Bench Pro (58.6%); SWE-bench Verified ~80.2%.
Kimi K2.7 Code	1T total / 32B active (MoE)	256K	June 12, 2026 NEW. Coding-focused build on K2.6 (Modified MIT) with a MoonViT vision encoder. Reports about +21.8% over K2.6 on Moonshot's own Kimi Code Bench v2 with roughly 30% fewer thinking tokens (vendor benchmark). API about $0.95 /$ 4.00 per 1M.
Kimi K2-Thinking-0905	-	-	First model to hit 100% on AIME 2025 (reasoning variant).

Best for: Long-horizon agent workloads, video understanding, open-weight agent stack alternative to closed frontier.

Alibaba Qwen 3.x Family - May 2026 NEW

Model	Parameters	License	Notes
Qwen3.8-Max	2.4T total / 95B active MoE	Qwen3.8-Max License (gated)	August 12, 2026. 262K context native, extensible to ~1,010,000. Open weights under a bespoke license, not Apache: attribution required above 100M MAU or $20M monthly revenue, and a separate paid license is required for Model-as-a-Service or AI-assistant businesses above$ 50M aggregate revenue. The open checkpoint is text-input-only; the API version is multimodal.
Qwen3.8-27B	27B dense	Apache 2.0	August 14, 2026. The more permissive and more modality-complete artifact: accepts image and video input where the open Max checkpoint does not. 262K context, extensible to ~1M. Dense rather than MoE, which makes it the practical single-GPU option.
Qwen 3.6 Max-Preview	~1T MoE	Commercial preview	Released ~April 20–27, 2026. 262K context. Tops six coding benchmarks per Alibaba.
Qwen 3.6-Plus	-	-	Released April 2, 2026. Enhanced coding.
Qwen 3.6-35B-A3B	35B / 3B active MoE	Apache 2.0	Released April 16, 2026. Open-weight workhorse.
Qwen2.5-Coder-32B	32B	Apache 2.0	Previous-generation open coding leader.
Qwen2.5-72B	72B	Apache 2.0	Previous-generation multilingual leader.
Qwen2.5-7B	7B	Apache 2.0	Efficient self-hosted option.

Mistral Family

Model	Parameters	Context	Notes
Mistral Medium 3.5	128B dense	256K	May 2026 NEW. Released April 29, 2026. Merges Magistral (reasoning) + Pixtral (vision) + Devstral 2 (coding) into one model. 77.6% on SWE-Bench Verified. $1.50/M input tokens.
Voxtral TTS	4B open-weights	streaming	May 2026 NEW (March 23 release, CC BY-NC 4.0). 70ms latency, 9 languages, 3-second voice cloning.
Mistral Large 3	675B (MoE, 41B active)	256K	Sparse MoE; parity with best open-weight models; #2 OSS non-reasoning on LMArena.
Mistral Small 4	-	256K	Hybrid instruct/reasoning/coding; released March 2026.
Mistral 3 (14B/8B/3B)	3B–14B	-	Unified family: multilingual, multimodal, Apache 2.0.
Mixtral 8x22B	141B (MoE)	-	Previous gen; still viable for throughput.

Google Gemma Family - May 2026 NEW

Model	Parameters	Context	License	Notes
Gemma 4 (31B dense)	31B	256K	Apache 2.0	Released April 2, 2026. 140+ languages; native vision/audio; function calling.
Gemma 4 (26B-A4B MoE)	26B / 4B active	256K	Apache 2.0	Sparse MoE variant.
Gemma 4 E4B	8B	256K	Apache 2.0	Edge-suitable.
Gemma 4 E2B	5.1B / 2.3B active	256K	Apache 2.0	Smallest variant; mobile/embedded.
DiffusionGemma (26B-A4B MoE)	26B / ~4B active	256K	Apache 2.0	June 10, 2026 NEW. Google DeepMind's first open-weight text-diffusion model; denoises blocks of tokens in parallel for roughly 4x faster generation (1000+ tokens/sec on one H100). Lower quality than standard Gemma 4; aimed at low-latency and in-line editing.

Zhipu / Z.ai GLM Family - June 2026 NEW

Model	Parameters	Context	License	Notes
GLM-5.3	Post-trained on the same 744B / 40B-active base as GLM-5.2	1M	Weights withheld at launch	August 14, 2026 via the GLM Coding Plan. The entire gain comes from extended post-training rather than a new pretraining run, a useful datapoint on where capability now comes from. Z.ai says cyber capability grew faster than anticipated as post-training scaled, claims a CyberGym lead, and staged the open-weight release pending safety evaluation, targeting roughly two weeks out (around August 28, 2026).
GLM-5.2	744B total / 40B active (MoE)	1M	MIT	Coding-plan access June 13, 2026; open weights June 16-17. Built for long-horizon agentic coding and tool use. Reports SWE-Bench Pro 62.1 (ahead of GPT-5.5 at 58.6 on that benchmark) and a long-horizon coding score near the closed frontier; figures are vendor-reported. API roughly $1.40 /$ 4.40 per 1M; weights on Hugging Face.

Best for: Open-weight agentic coding and long-horizon tool use where a 1M context and a permissive license matter. Verify benchmark claims on independent leaderboards.

Thinking Machines Inkling - July 2026 NEW

Model	Parameters	Context	License	Notes
Inkling	975B total / 41B active (MoE)	1M (64K or 256K via the lab's Tinker API)	Open weights	Released July 15, 2026: Thinking Machines Lab's first public model, pretrained on 45T tokens of text, image, audio, and video. SWE-Bench Verified 77.6%; the leading US open-weights model per Artificial Analysis, with safety scores the lab reports as aligning with frontier models. NVFP4 checkpoint optimized for NVIDIA Blackwell.
Inkling-Small (preview)	276B total / 12B active	-	Open weights	Announced alongside Inkling for lower cost and latency.

Why it matters: A brand-new US lab shipping the leading American open-weights model, positioned explicitly as a fine-tuning foundation. Until July the open frontier was dominated by Chinese labs; Kimi K3 and Inkling landing in the same week is the strongest open-weights month on record.

Meta Muse Spark (Closed Weights) - May 2026 STRATEGIC SHIFT

Attribute	Value
License	Closed weights - first proprietary model from Meta Superintelligence Labs
Capabilities	Multimodal reasoning with Instant / Thinking / Contemplating modes
Released	April 8, 2026

Strategic significance: Meta's first non-open model since the original Llama era. Signals that frontier-quality work may require a closed-development feedback loop. Llama 4 Behemoth release was simultaneously paused through fall 2026 amid capability concerns. The open-vs-closed equilibrium is now two-tier: frontier closed lags 6–12 months ahead; open weights catch up via distillation, RL, and ecosystem iteration.

July 2026 update: Muse Spark 1.1 shipped July 9 alongside the public preview of the Meta Model API, Meta's first self-serve paid API: OpenAI-compatible, $1.25 /$ 4.25 per 1M, roughly a quarter of rival flagship rates. Vendor-reported benchmarks lead on scaled tool use (MCP Atlas 88.1) and professional tool use (JobBench 54.7). Meta charging for API access completes the pivot away from open-weight Llama; there is no Llama 5, and Behemoth remains shelved.

August 2026 update: Muse Glimmer (August 10) is Meta's first open-weight release since Llama 4 and, at Apache 2.0, its most permissive license ever for an open model. It is a 30B dense multimodal model aimed at always-on local agent work (local coding agents, function calling, LLM-as-a-judge), with a 131,072-token context; quantized to 4-bit it fits under 20GB and runs on a single 24GB consumer GPU. Muse Spark 1.2 and Muse Code, a terminal coding agent, shipped alongside it, notable for a muse-spark-1.2-contributor tier priced at $0.10 /$ 0.20 per 1M (against $1.25 /$ 4.25 standard) in exchange for permission to train on your prompts and completions. Data-for-discount as an explicit, published API tier is new, and worth a policy decision before anyone enables it.

The August 2026 Open-Weight Licensing Split

August was the month open weights stopped meaning one thing. Three postures now coexist, and the license is as much a design input as the benchmark:

Model	Released	Size	License posture	What the license actually does
Qwen3.8-Max (Alibaba)	Aug 12	2.4T / 95B active	Bespoke, commercially gated	Free use, modification, and resale, but attribution is required above 100M MAU or $20M monthly revenue, and a separate paid license is required to run a Model-as-a-Service or AI-assistant business above$ 50M aggregate revenue
Qwen3.8-27B (Alibaba)	Aug 14	27B dense	Apache 2.0	No conditions. The smaller sibling is both more permissive and more modality-complete than the flagship
Muse Glimmer (Meta)	Aug 10	30B dense	Apache 2.0	No conditions; Meta's most permissive open license to date
Tencent Hy3	Global Aug 5 (model Jul 6)	295B / 21B active	Apache 2.0	Fully permissive with no geographic carve-outs, reversing the April preview's restrictive license that excluded the EU, UK, and South Korea
Ling-3.0-flash / tiny (Ant Group)	Aug 5 / Aug 11	124B / 5.1B active; 7.9B / 1.3B active	MIT	No conditions
Nemotron 3.5 Lightning (NVIDIA)	Aug 11	30B / 3B active	OpenMDW-1.1	Linux Foundation license, free for commercial use
GLM-5.3 (Z.ai)	Aug 14	744B base	Weights withheld	Open release deliberately staged pending safety evaluation after cyber capability grew faster than expected; Z.ai gave a target of roughly two weeks (around August 28, 2026)

Two things follow for anyone building on open weights. First, read the license before the model card: a gated license can make a "open" flagship unusable for exactly the SaaS business you were planning, while its smaller sibling is unencumbered. Second, withholding is now a legitimate outcome: a lab can ship a model commercially and hold the weights on safety grounds. Z.ai did publish a target date, so treat it as a dated plan rather than an open-ended promise, and do not build a roadmap on weights that have not shipped.

Small and On-Device Models - August 2026

Model	Size	Context	License	Notes
Ling-3.0-tiny (Ant Group)	7.9B / 1.3B active	256K	MIT	Genuinely laptop-class agentic model: roughly 8.3 GiB peak memory at 8K context, 86-90 tok/s on an M4 Pro MacBook at FP8
LFM2.5-2.6B (Liquid AI)	2.6B	128K	Open weights	Built for on-device tool calling and multi-step planning rather than chat; under 2.5 GB memory, runs down to a Raspberry Pi
LFM2.5-VL-3B (Liquid AI)	3B	-	Open weights	On-device vision-language model for screen understanding and GUI grounding (August 12)
Shieldstral 1.0 (Mistral)	3B	32K	Apache 2.0	Policy-adaptive multimodal safety classifier (text and image, 12 languages): moderation policies are supplied in natural language at inference time, so a policy change needs no retraining. Runs on one 16GB GPU
Muse Glimmer (Meta)	30B dense	131K	Apache 2.0	Under 20GB at 4-bit; targets always-on local agents

The pattern worth noting: the small-model tier stopped competing on chat quality and started competing on tool calling, planning, and screen grounding, which are the capabilities a local agent actually needs.

Specialized Models

Coding Mastery (June 2026)

Model	Specialization	Why it wins
Claude Fable 5	Capability ceiling	Mythos-class coding now generally available; highest frontier score on Cognition's FrontierCode and SOTA on CursorBench per Anthropic; 2x Opus 4.8 price
GPT-5.5	Single-shot coding leader (published)	SWE-bench Verified 88.7%; Terminal-Bench 2.1 78.2%
Claude Opus 4.8	Long-running agentic coding	SWE-bench Verified 88.6%; SWE-Bench Pro 69.2%; Dynamic Workflows with parallel subagents in Claude Code
Claude Opus 4.7	Predecessor flagship coding	SWE-bench Verified 87.6%; SWE-Bench Pro 64.3%
Claude Sonnet 4.6	Workhorse coding	Powers Claude Code at lower cost; 1M context
Llama 4 Maverick	Open-source coding	Open weights; competitive on coding benchmarks
Qwen 3.6 Coder / Qwen2.5-Coder-32B	Self-hosted coding	Best price-to-performance for self-hosted IDEs
DeepSeek V4 Pro / R1-Distill-70B	Open reasoning + code	Best open reasoning at 70B; V4 Pro is open-weight 1.6T/49B-active MoE
Z.ai GLM-5.2	Open agentic coding	June 2026; 744B / 40B-active MoE, 1M context, MIT; reports SWE-Bench Pro 62.1 ahead of GPT-5.5 on that benchmark (vendor-reported); about $1.40 /$ 4.40 per 1M
Kimi K2.7 Code	Open long-horizon coding	June 2026; 1T / 32B-active MoE, Modified MIT; tuned from K2.6 for software work with fewer thinking tokens
Cohere North Mini Code 1.0	Open lightweight coding	June 2026; 30B / 3B-active MoE on a single H100, Apache 2.0; Cohere's first open coding model

Reasoning & Math

Model	Approach	Best For
Claude Fable 5	Always-on adaptive thinking at the Mythos capability tier	The hardest reasoning problems where ceiling beats cost
Claude Opus 4.8 (thinking)	Adaptive thinking with parallel subagents	Software planning, codebase-scale work, agentic reasoning
GPT-5.5 reasoning	Maximum-compute reasoning	Competition math (AIME 2025 81.2% on Instant), ARC-AGI-2 85.0% leader
Gemini 3.1 Pro Deep Think	Sustained chain-of-thought	Scientific reasoning, GPQA Diamond leader
DeepSeek-R1	RL-based thinking	Open-source logical inference, competitive math
Grok 4.3 (DeepSearch)	Web-grounded reasoning	Research tasks needing live information

Long Context (1M+)

Model	Window	Recall Performance
Llama 4 Scout	10M	Industry-leading open-weight context window
Gemini 3.1 Pro / Flash	1M	Best quality at 1M context; proven at scale
Claude Fable 5	1M	Anthropic reports improved long-context performance with persistent memory across long sessions
Claude Opus 4.8 / 4.7 / Sonnet 4.6	1M	Full 1M at standard pricing; reliable recall
Llama 4 Maverick	1M	Open-weight 1M context with MoE efficiency

Embedding Models

API Embedding Models (May 2026)

Model	Dimensions	Max Tokens	MTEB Score	Cost/1M
OpenAI text-embedding-3-large	3072	8191	64.6	$0.13
OpenAI text-embedding-3-small	1536	8191	62.3	$0.02
Voyage-3	1024	32000	67.8	$0.06
Cohere embed-v3	1024	512	66.4	$0.10
Google text-embedding-004	768	2048	66.1	$0.025

Open Source Embedding Models

Model	Dimensions	Max Tokens	MTEB	Notes
BGE-large-en-v1.5	1024	512	63.9	Instruction-tuned
E5-mistral-7b-instruct	4096	32768	66.6	Strong with instructions
Nomic-embed-text-v1.5	768	8192	62.3	Long context, open
GTE-Qwen2-7B	3584	32K	72.1	State-of-the-art open embedding

Embedding Selection Guide

Requirement	Recommended	Why
Best quality	Voyage-3 or text-embedding-3-large	Highest MTEB
Cost-efficient	text-embedding-3-small	$0.02/1M
Self-hosted	GTE-Qwen2-7B	Best open MTEB
Long documents	Nomic or Voyage-3	8K+ context
Multilingual	Cohere embed-v3	Built for multilingual

Model Selection Framework

Decision Tree

What is your primary constraint?

├── Cost → Use smaller model, consider open source
│   ├── Very cost sensitive → DeepSeek V4 Flash, GPT-5.5-mini, Claude Haiku 4.5, Gemini 3.1 Flash
│   └── Moderate budget → Claude Sonnet 4.6, GPT-5.5 Instant, DeepSeek V4 Pro
│
├── Quality + Reasoning → Use frontier models
│   ├── Highest reasoning → Claude Fable 5, Claude Opus 4.8 (thinking), GPT-5.5 reasoning, Gemini 3.1 Pro Deep Think
│   └── Coding + reasoning → Claude Opus 4.8 with Dynamic Workflows, Claude Sonnet 4.6 (Extended Thinking), GPT-5.5
│
├── Latency → Use fast models
│   ├── <100ms response → Gemini 3.1 Flash, GPT-5.5-mini
│   └── <500ms response → Claude Haiku 4.5, Claude Opus 4.8 fast mode, Grok 4.1 Fast
│
├── Self-hosting → Use open models
│   ├── Maximum capability → Llama 4 Maverick, DeepSeek-V3
│   ├── Good balance → Llama 4 Scout, Llama 3.3 70B, Qwen2.5-72B
│   └── Edge/mobile → Mistral 3 3B, Phi-4
│
└── Privacy → Self-host or use on-prem
    └── Choose open models with appropriate license

Semantic Routing

Static decision trees are being replaced by Semantic Routers:

How it works: A small, fast embedding model vectorises the query. If it matches a "known easy" cluster, route to a cheap model (Gemini 3.1 Flash, DeepSeek V4 Flash, Claude Haiku 4.5). If it hits an "agentic/logic" cluster, route to Claude Opus 4.8 or GPT-5.5 with reasoning.
Benefit: Automates cost-optimization without hardcoded rules.
Implementation: Tools like semantic-router (Python) or custom Weaviate/Pinecone classifiers.

Sovereign AI and Data Residency

The 2026 Regulatory Reality: Enterprises must comply with GDPR (EU), DPDPA (India), Saudi Arabia PDPL, and sectoral rules. "Sovereign AI" is now a product category.

Solution	Provider	Use Case
Azure Government/Sovereign	Microsoft	Dedicated infra in 40+ regions; approved for US Gov/EU NIS2
AWS Sovereign Cloud	Amazon	Physically isolated VPCs; GDPR-safe EU regions
Google Distributed Cloud	Google	Air-gapped on-prem Gemini deployment
Private Llama 4 / 3.3	Meta (self-host)	Maximum data sovereignty; open weights (Llama 4 MoE or 3.3 dense)
DeepSeek (self-host)	DeepSeek (open)	Open weights; no data leaves your infra
Mistral Large 3 (self-host)	Mistral (Apache 2.0)	675B MoE; open weights; strong multilingual

Tradeoff: Sovereign clouds carry a 20-30% premium over standard global regions but are mandatory for finance and government.

Cost Comparison at Scale (May 2026)

Assume 1M requests/day, 1K input + 500 output tokens:

Model	Input Cost/Day	Output Cost/Day	Total/Month
Claude Sonnet 4.6	$3,000	$7,500	$315,000
GPT-5.4	$2,500	$7,500	$300,000
Gemini 3.1 Pro	$2,000	$6,000	$240,000
GPT-5.4-mini	$750	$2,250	$90,000
Gemini 3.1 Flash	$100	$1,500	$48,000
Self-hosted Llama 4 Scout*	-	-	~$15,000
Self-hosted Llama 3.3 70B*	-	-	~$50,000

*Self-hosted Llama 4 Scout fits on a single H100; Llama 3.3 70B assumes 4x H100 GPUs

Capability Comparison

Benchmark Performance (May 2026)

Model	MMLU	HumanEval	SWE-bench Verified	Notes
Claude Opus 4.6	-	-	-	Top-tier across reasoning and coding; specific scores check latest
GPT-5.4	-	-	-	33% fewer factual errors vs GPT-5.2; strong coding + agentic
Claude Sonnet 4.6	-	-	-	Approaches Opus-level on many tasks
Gemini 3.1 Pro	-	-	-	State-of-the-art Google reasoning
Grok 4	-	-	-	Competitive reasoning; real-time web integration
Llama 4 Maverick	-	-	-	Beats GPT-4o, Gemini 2.0 Flash on reported benchmarks
DeepSeek-R1	90.8	92.6	49.2%	First open-source reasoning model; math/code strong

Source: Respective technical reports and LMSYS Chatbot Arena / LMArena, April 2026. Benchmark scores for newest models (Opus 4.6, GPT-5.4, Gemini 3.1) are evolving rapidly -- always verify with current leaderboards.

Task-Specific Recommendations (May 2026)

Task	Recommended Models	Why
Autonomous Coding Agent	Claude Sonnet 4.6 / Opus 4.6	Powers Claude Code; 1M context; top tool reliability
Complex Reasoning	GPT-5.4 Pro, Claude Opus 4.6 (thinking), DeepSeek-R1	Maximum reasoning power
Agentic Computer Use	GPT-5.4	First general-purpose model with native computer-use capabilities
High-Volume API	Gemini 3.1 Flash, GPT-5.4-mini	Lowest cost per token in class
Long Context RAG	Gemini 3.1 Pro/Flash (1M), Claude Sonnet 4.6 (1M)	Verified long-range recall
Ultra-Long Context	Llama 4 Scout (10M)	Industry-leading 10M context; open weights
Multimodal Real-time	Gemini 3.1 Flash	Real-time audio/video/text native
Private Production	Llama 4 Maverick, Llama 3.3 70B, Qwen2.5-72B	High capability with local control
Open-source Coding	Llama 4 Maverick, Qwen2.5-Coder-32B	Open weights, strong coding benchmarks
Creative/Chat	GPT-5.4	Strong conversation quality and instruction following

Interview Questions

Q: How would you select a model for a production RAG system?

Strong answer: I evaluate across these dimensions:

1. Quality requirements:

Test on representative queries from the actual domain
Measure answer correctness, hallucination rate, citation accuracy

2. Cost analysis:

Monthly cost = requests/day × 30 × avg_tokens × rate

Always calculate for top 2-3 candidates.

3. Latency requirements:

If <200ms TTFT needed: Gemini 3.1 Flash, Claude Haiku 4.5, GPT-5.4-mini
If quality is paramount: Accept 2-3s with Claude Opus 4.6 or GPT-5.4

4. Operational requirements:

Self-hosting: Llama 4 Scout/Maverick, DeepSeek-V3
Compliance / data residency: Azure Sovereign or self-hosted

5. Practical selection:

Start with Claude Sonnet 4.6 or GPT-5.4 for prototyping
A/B test Gemini 3.1 Flash for 80% of queries (cost)
Keep frontier on hard queries via semantic routing

Q: Explain the tradeoffs between proprietary and open source models.

Strong answer:

Factor	Proprietary (OpenAI, Anthropic)	Open Source (Llama, DeepSeek)
Quality	Generally higher (slightly)	Catching up rapidly
Cost	Per-token pricing	Compute + ops
Control	Limited	Full
Privacy	Data goes to provider	Stays on-prem
Updates	Automatic	Manual
Customization	Limited fine-tuning	Full fine-tuning
Ops overhead	None	Significant

Key insight (2026): DeepSeek-V3/R1 and now Llama 4 have changed this conversation -- open models match or beat GPT-4o on many benchmarks. With Llama 4 Maverick matching DeepSeek V3 on reasoning at half the active parameters, the gap is narrower than ever.

Q: What is the difference between GPT-5.4 Pro and Claude Opus 4.6's Extended Thinking?

Strong answer: Both use internal chain-of-thought, but the mechanics differ:

GPT-5.4 Pro: OpenAI's maximum-compute reasoning tier ( $30/$ 180 per 1M tokens). Allocates high compute to reasoning. Internal thoughts are not exposed. Successor to the o3 line.
Claude Opus 4.6 Adaptive Thinking: Returns thinking tokens in a separate <thinking> block. Configurable budget_tokens. You can inspect the reasoning chain for debugging. Full 1M context with 128K max output.

Production choice: For debugging and trust-building, Claude's visible thinking is more transparent. For maximum raw reasoning power on math/competition tasks, GPT-5.4 Pro leads. For cost-effective reasoning, Claude Sonnet 4.6 or GPT-5.4-mini are strong choices.

References

Anthropic: https://platform.claude.com/docs/en/about-claude/models/overview
OpenAI Platform: https://developers.openai.com/api/docs/models
Google AI: https://ai.google.dev/gemini-api/docs/models
Meta Llama: https://www.llama.com/
DeepSeek: https://api-docs.deepseek.com/
xAI Grok: https://docs.x.ai/developers/models
Mistral AI: https://docs.mistral.ai/models/
LMArena Leaderboard: https://lmarena.ai/
Hugging Face Open LLM Leaderboard: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard

Next: Capability Assessment