Find the right model for the work

Meta's updated multimodal reasoning model for coding, tool use, computer interaction, and multi-agent workflows. [Muse Spark 1](/meta/muse-spark/1) gains a 1M-token context window and broader availability through the Meta Model API public preview and Meta AI's Thinking mode.

SpaceXAI's frontier model for coding, agentic tasks, and knowledge work, succeeding [Grok 4.1 Fast](/xai/grok/4-1-fast). Grok 4.5 runs at up to 80 tokens per second, uses roughly half as many tokens as comparable models on agentic tasks, and is available in Grok Build, Cursor, and the API.

Poolside's upgraded 33B-total, 3B-active local coding model improves multilingual and terminal-style agent work while retaining a 256K context window. It ships with open weights under OpenMDW 1.1 and paid API pricing of $0.10/M input and $0.20/M output tokens.

Anthropic's most agentic Sonnet yet: top-tier coding and tool use at Sonnet pricing with a 1M context window. Performance is close to [Claude Opus 4.8](/anthropic/opus/4-8) on agentic benchmarks, with a substantial upgrade over [Claude Sonnet 4.6](/anthropic/sonnet/4-6) on reasoning, tool use, coding, and knowledge work. Default model on Free and Pro plans and new default in Claude Code for Pro users. Introductory API pricing of $2/M input and $10/M output through August 31, 2026, then standard $3/$15; available as claude-sonnet-5 on the Claude Platform.

OpenAI's strongest model yet and flagship of the new GPT 5.6 tier naming: the generation number (5.6) advances on its own cadence while Sol, Terra, and Luna are durable capability tiers. State-of-the-art on Terminal-Bench 2.1 for agentic command-line coding; stronger GeneBench v1 genomics results than [GPT 5.5](/openai/gpt/5-5) with fewer tokens; on ExploitBench² competitive with [Claude Mythos Preview](/anthropic/mythos/preview) using roughly one-third of the output tokens. Introduces max reasoning effort and ultra mode (parallel subagents). Ships with OpenAI's most robust safety stack to date. Limited preview via API and Codex for trusted partners; broader ChatGPT and API availability planned in coming weeks. API pricing $5/M input and $30/M output, matching the prior [GPT 5.5](/openai/gpt/5-5) flagship. Positioned against [Claude Fable 5](/anthropic/fable/5) and [Claude Mythos 5](/anthropic/mythos/5) on frontier agentic and cyber workloads.

OpenAI's balanced GPT 5.6 tier for everyday work: performance competitive with [GPT 5.5](/openai/gpt/5-5) at half the API cost ($2.50/M input, $15/M output). Part of the durable Sol/Terra/Luna family where Terra sits between flagship [GPT Sol 5.6](/openai/gpt-sol/5-6) and affordable [GPT Luna 5.6](/openai/gpt-luna/5-6). Strong improvements on ExploitGym cyber benchmarks as reasoning effort increases. Analogous to Anthropic's balanced frontier lines such as [Claude Opus 4.8](/anthropic/opus/4-8) and [Claude Sonnet 4.6](/anthropic/sonnet/4-6) for cost-performance everyday agentic work, while Sol targets [Claude Fable 5](/anthropic/fable/5) / [Mythos 5](/anthropic/mythos/5) territory. Limited preview via API and Codex with general availability planned soon.

OpenAI's fast, affordable GPT 5.6 tier: strong capability at the lowest cost in the family ($1/M input, $6/M output). Completes the durable Sol/Terra/Luna lineup alongside [GPT Sol 5.6](/openai/gpt-sol/5-6) (flagship) and [GPT Terra 5.6](/openai/gpt-terra/5-6) (balanced). All three GPT 5.6 tiers show strong ExploitGym cyber improvements as reasoning scales. Positioned as OpenAI's volume tier, comparable in role to [Claude Haiku 4.5](/anthropic/haiku/4-5) for low-latency, cost-sensitive workloads, while [GPT 5.5](/openai/gpt/5-5) remains the prior-generation unified flagship on the legacy GPT product line. Limited preview via API and Codex.

Experimental open Gemma model that generates text via diffusion instead of autoregressive decoding. 26B MoE (3.8B active) built on Gemma 4 and Gemini Diffusion research, released under Apache 2.0. Delivers up to 4x faster token generation on dedicated GPUs (1000+ tok/s on H100, 700+ on RTX 5090) by drafting 256-token blocks in parallel with bi-directional attention. Fits in 18GB VRAM when quantized. Best for speed-critical local workflows like in-line editing, code infilling, and rapid iteration; standard Gemma 4 remains recommended for maximum output quality.

Anthropic's first generally available Mythos-class model: state-of-the-art on software engineering, knowledge work, vision, and scientific research, with the largest lead over prior Claude models on long, complex tasks. Ships with safety classifiers that route some cybersecurity, biology, and distillation queries to Opus 4.8 (triggering in under 5% of sessions on average). Available on the Claude API as claude-fable-5, Claude apps, and major cloud platforms at $10/M input and $50/M output.

Same underlying model as Claude Fable 5 with cyber safeguards lifted for vetted partners. Strongest cybersecurity capabilities of any model in the world at launch, deployed through Project Glasswing as an upgrade to Mythos Preview. Restricted to Glasswing partners initially, with a broader trusted access program planned. API pricing at $10/M input and $50/M output.

Cohere's first dedicated agentic coding model is a 30B-total, 3B-active open MoE for repository changes, terminal work, and local deployment. It ships with a 256K context window, 64K maximum output, tool use, structured output, and Apache 2.0 weights.

Microsoft AI's flagship MoE reasoning model (~35B active, ~1T total parameters) for math, coding, and enterprise workloads. Competitive with Claude Opus 4.6 on SWE-Bench Pro at a smaller inference footprint, preferred to Sonnet 4.6 in blind Surge human evals, with built-in safety guardrails and copyright protection. Available in Microsoft Foundry private preview.

5B-parameter inference-efficient agentic coding model custom-trained for GitHub Copilot and VS Code. Plans and reasons through multi-step coding tasks, supports broad language ecosystems, and is positioned as comparable to Claude Haiku at lower cost. Rolling out in GitHub Copilot in VS Code.

Text-to-image and image-editing model for photorealistic, design-ready output with fine-grained edit control, reliable text rendering, and branding or product workflows. Includes an ultra-efficient Flash variant; Microsoft reports Arena scores surpassing Nano Banana Pro. Available via MAI Playground and Microsoft Foundry.

Speech-to-text model with 4.9% average WER on FLEURS across 43 languages (automatic detection), contextual biasing for domain terminology, and ~5.7x lower latency than cited competitors. Outperforms Scribe v2, Whisper-large-v3, GPT-4o-Transcribe, and Gemini 3.1 Flash on many language benchmarks. Priced at $0.36 per hour via Azure Speech / Foundry.

Multilingual text-to-speech with 15 languages, instant voice matching from short reference clips, expressive emotion control, and stable long-form output for audiobooks, podcasts, and lectures. Built-in guardrails require authorized, consented voices. Priced at $0.22 per 1M characters via MAI Playground and Azure Speech.

12B-parameter Mixture-of-Experts focal model (2.5B active per token) for routing, RAG, sub-agents, and private deployments. Ships open from day one with base, instruct, and thinking checkpoints under Apache 2.0.

MiniMax's open-weight multimodal frontier model combines coding, agentic computer use, image and video input, and long-context work. Its MiniMax Sparse Attention architecture supports up to one million tokens while improving prefill and decoding efficiency over the M2 generation.

Upgrade to Anthropic's Opus class with stronger performance across coding, agentic tasks, and professional work, plus improved consistency for long-running tasks. Adds effort control in claude.ai and Cowork, dynamic workflows in Claude Code (research preview) for large parallel subagent runs, and fast mode at 2.5x speed with pricing three times lower than on prior Opus models. Same standard API pricing as Opus 4.7 ($5/M input, $25/M output). Available via Claude API as claude-opus-4-8.

Cohere's 218B-total, 25B-active open MoE unifies reasoning, vision, multilingual work, and tool use in one enterprise model. It supports 48 languages, 128K input, 64K output, and Apache 2.0 weights that can run on a single B200 or two H100 GPUs.

Qwen3.7-Max agent foundation with 1M-token context, long-horizon tool use, and frontier coding and office automation scores.

Gemini 3.5 Flash is Google's agentic and coding-focused Flash model: frontier-class scores on Terminal-Bench 2.1 (76.2%), GDPval-AA, and MCP Atlas at roughly 4x the output tokens per second of other frontier models.

128B dense Mistral flagship with 256K context, multimodal inputs, and configurable reasoning_effort for chat versus agentic coding.

NVIDIA's open 30B-total, 3B-active omni model combines reasoning over text, images, video, and audio for document intelligence, computer use, and multimodal agents. NVIDIA released the model with open weights, training data, and recipes, plus a 256K context window and 64K maximum output.

Poolside's 225B-total, 23B-active flagship MoE for long-horizon coding agents launched alongside the Laguna runtime and agent experiences. It targets multi-file debugging, repository exploration, tool use, and validated software changes with a 256K served context window.

Poolside's compact 33B-total, 3B-active coding MoE brought the Laguna family to local machines with Apache 2.0 open weights. It supports reasoning, tool use, a 256K served context window, and long-horizon software engineering workflows.

MoE Qwen3.6 35B-A3B open-weight checkpoint with efficient active parameters for local and cloud inference.

Dense Qwen3.6 27B model for strong reasoning and coding at a mid-size parameter budget.

The flagship variant of the [DeepSeek V4](/deepseek/deepseek/v4) family, with 1M-token context, frontier reasoning, long-context coding, and competitive scores on agentic engineering benchmarks.

Lower-latency variant of [DeepSeek V4](/deepseek/deepseek/v4), tuned for high-throughput chat, tool loops, and cost-sensitive agent deployments with a 1M-token context window.

DeepSeek's open-source V4 Preview family introduces cost-efficient 1M-token context for long-horizon coding and agentic work. It succeeds [DeepSeek V3.2](/deepseek/deepseek/v3-2) and ships as the fast [V4-Flash](/deepseek/deepseek/v4-flash) and flagship [V4-Pro](/deepseek/deepseek/v4-pro) variants.

OpenAI's smartest general-purpose frontier model for agentic coding, computer use, and knowledge work. State-of-the-art on Terminal-Bench 2.0 (82.7%), SWE-Bench Pro (58.6%), Expert-SWE (73.1%), GDPval (84.9%), OSWorld-Verified (78.7%), and BrowseComp (84.4%). Matches GPT-5.4 per-token latency while using fewer tokens on Codex tasks. Rolling out in ChatGPT and Codex; API pricing at $5/M input and $30/M output with 1M context.

Open-weight coding and agent model from Moonshot AI. Reported SOTA among open models on Humanity's Last Exam with tools (54.0%), SWE-Bench Pro (58.6%), and strong scores on SWE-bench Multilingual (76.7%), BrowseComp (83.2%), Toolathlon (50.0%), CharXiv with Python (86.7%), and MathVision with Python (93.2%). Positioned for GPT-5.4-class coding at much lower cost than closed frontier APIs, with long-horizon runs (4,000+ tool calls, 12+ hours), large agent swarms (300 parallel sub-agents, 4,000 steps per run), and multimodal front-end capabilities. Available on kimi.com (chat and agent mode); Kimi Code at kimi.com/code targets production workflows.

Latest version of Anthropic's most capable model, continuing the frontier model line with improvements in reasoning, coding, and agentic capabilities.

Meta's first Muse family model, a natively multimodal reasoning system for visual chain-of-thought, tool use, coding, and multi-agent orchestration. It complements Meta's open [Llama 4 Maverick](/meta/llama/4-maverick) line with an agent-focused model available through Meta AI and an API preview.

First Mythos-class frontier model, announced through Project Glasswing for defensive cybersecurity with AWS, Google, Microsoft, and other partners. Not generally available: restricted to vetted critical-infrastructure and security organizations. Demonstrated autonomous vulnerability discovery surpassing skilled humans; priced at $25/M input and $125/M output for partners.

Gemma 4 ships under Apache 2.0 with multimodal vision and audio on select sizes, up to 256K context on larger checkpoints.

Qwen 3.6 Plus balances reasoning, multimodal understanding, and agent tooling for production assistants on DashScope.

MiniMax M2.7 text API model focused on software engineering, office suites, and complex agent skills with strong SWE-Pro and GDPval-AA scores.

MiniMax-M2.7 improves end-to-end project delivery, log analysis, and complex agent harnesses; ~56% SWE-Pro and strong Terminal-Bench 2 scores among open models.

High-TPS variant of MiniMax-M2.7 with identical results to M2.7 at faster speed for agent and coding APIs.

Efficient Mistral Small 4 models for low-latency assistants, on-device style deployments, and cost-sensitive APIs.

OpenAI's most capable frontier model with 1M token context (Codex/API), native computer-use, and top benchmarks: SWE-Bench Pro 57.7%, OSWorld-Verified 75% (beats human 72.4%), BrowseComp 82.7%, GDPval 83%, Toolathlon 54.6%. More token-efficient and faster reasoning than 5.2.

Google's latest Gemini model designed for complex tasks where a simple answer isn't enough. Builds on the Gemini 3 family with enhanced reasoning and deeper analysis capabilities for sophisticated computational challenges.

Full upgrade across coding, computer use, long-context reasoning, agent planning, and knowledge work. Features 1M token context window (beta) and significant improvements in consistency and instruction following. Users prefer it to Sonnet 4.5 roughly 70% of the time, and over Opus 4.5 59% of the time — approaching Opus-level intelligence at $3/$15 per million tokens.

OpenAI's fastest coding model yet. Built on the Codex line, Codex Spark prioritizes speed and low-latency responses while retaining strong coding performance - ideal for real-time pair-programming and interactive development workflows.

MiniMax-M2.5 targets real-world productivity: 80.2% SWE-Bench Verified, strong agentic search and office tasks, and ~37% faster than M2.1 on SWE-Bench Verified runs.

Higher-throughput M2.5 variant with the same capabilities as MiniMax-M2.5 at faster output token rates for latency-sensitive agent workloads.

Google's specialized reasoning mode for science, research, and engineering. Uses iterative rounds of reasoning to explore multiple hypotheses simultaneously. Achieves 48.4% on Humanity's Last Exam (without tools) and 84.6% on ARC-AGI-2. Demonstrates gold medal-level results on the 2025 International Physics and Chemistry Olympiads.

Zhipu AI's open-weight 744B parameter MoE model (40B active per token) trained on 28.5T tokens. First open model to score 50+ on the Artificial Analysis Intelligence Index v4.0, outperforming Gemini 3.0 Pro and GPT-5.2 across multiple benchmarks. Released under MIT License.

Major update with 1M token context window (beta), improved coding and debugging capabilities, enhanced reasoning with adaptive thinking, and new agent teams feature in Claude Code.

OpenAI's latest coding-focused model with best-in-class coding performance (57% SWE-Bench Pro, 76% TerminalBench 2.0, 64% OSWorld). Features customizable personality modes ('pragmatic' or 'friendly'), mid-task steerability with live updates, and the first model to achieve 'high' rating for cybersecurity on OpenAI's preparedness framework. Significantly faster and more efficient—uses less than half the tokens of 5.2-Codex for equivalent tasks and runs >25% faster per token.

Iterative Kimi K2 release with improved agent reliability, multimodal inputs, and coding scores ahead of the K2.6 line.

Refined M2 line with better multi-step tool reliability and higher scores on coding agent benchmarks.

Devstral 2 coding model for IDE agents and the Mistral Vibe CLI with stronger repository-scale refactors than Devstral 1.

DeepSeek V3.2 upgrade with stronger reasoning, tool use, and coding performance on the V3 architecture.

Faster, lower-latency Grok 4.1 variant for real-time assistants and high-throughput API workloads.

Iterative Grok release focused on emotional intelligence, creative writing, and reduced hallucinations versus Grok 4.

Reasoning-focused Kimi K2 variant with extended thinking time for hard math, code, and planning tasks.

MiniMax M2 open-weight model focused on coding agents, tool use, and cost-efficient inference.

Haiku 4.5 targets near-frontier coding and agent quality with a much smaller compute footprint than Sonnet-class models.

Anthropic's coding- and agent-focused Sonnet with checkpoints in Claude Code, computer-use gains, code execution in Claude apps, and the same $3/$15 pricing as Sonnet 4.

Cost-efficient Grok 4 generation model with a 2M-token context window and faster responses for high-volume chat and tool use.

OpenAI's unified GPT-5 system with adaptive reasoning, state-of-the-art performance across coding, math, writing, and health, available across ChatGPT tiers and the API.

Upgrade to Claude Opus 4 with 74.5% SWE-bench Verified, stronger agentic search, and improved multi-file refactoring at the same Opus 4 API pricing.

Open-weight Kimi K2 MoE model aimed at agentic coding and tool use, with competitive scores on SWE-bench style tasks.

SpaceXAI's Grok 4 flagship with native tool use, real-time search, and strong reasoning on math, science, and coding benchmarks.

Higher-compute Grok 4 variant aimed at the hardest reasoning, math, and agentic workloads in the Grok 4 generation.

Higher-compute o3 configuration that thinks longer for maximum reliability on the hardest reasoning and agentic tasks.

Next-generation Claude Opus with leading coding performance, hybrid instant and extended thinking modes, and improved agent workflows in Claude Code.

Claude Sonnet 4 hybrid model with instant and extended thinking modes, 72.7% SWE-bench Verified, and sharper instruction following versus Sonnet 3.7.

OpenAI's o3 reasoning model with agentic tool use in ChatGPT, combining web search, Python, vision, and image generation in a single reasoning stack.

OpenAI API-only GPT-4.1 family (4.1, 4.1 mini, 4.1 nano) with 1M-token context, stronger coding and instruction following than GPT-4o, and June 2024 knowledge cutoff.

Meta Llama 4 Scout multimodal MoE model (17B active) with native image and video understanding and a 10M-token context window.

Meta Llama 4 Maverick flagship MoE (17B active, 400B total) with leading open multimodal benchmarks versus prior Llama generations.

Google's first Gemini 2.5 thinking model, topping major reasoning and coding benchmarks with a 1M token context window at launch.

Cohere's 111B open-weight enterprise model for agentic workflows, retrieval, multilingual work, and tool use. Command A launched with a 256K context window and was designed to run on two GPUs while competing with substantially larger models.

Gemma 3 adds multimodal understanding (except 1B), 128K context, and 140+ language support across 1B-27B sizes.

OpenAI's largest GPT chat model at launch, scaled for broader knowledge, improved alignment, and more natural conversation with fewer hallucinations than GPT-4o, without o-series chain-of-thought reasoning.

Anthropic's first hybrid reasoning Sonnet with visible extended thinking, strong coding and agentic gains, and fine-grained thinking budget control in the API.

Experimental Gemini 2.0 Pro focused on agentic capabilities, native multimodality, and faster responses for developers on Vertex AI and Google AI Studio.

Moonshot's multimodal Kimi K1.5 with long-context reasoning and strong math and coding scores on public leaderboards.

Gemini 2.0 Flash Experimental added native tool use and multimodal output for agentic applications while improving speed over Gemini 1.5 Pro.

Meta's 70B instruct Llama with post-training refinements that match Llama 3.1 405B quality on many benchmarks at far lower serving cost, with 128K context.

Full o1 reasoning model with multimodal inputs, faster responses than o1-preview, and fewer major errors on hard reasoning tasks.

Upgraded Haiku with improved instruction following, tool use, and coding versus Claude 3 Haiku, while staying in the same low-latency tier.

JetBrains' first focal model: a 4B-parameter LLM trained from scratch for multilingual cloud code completion in JetBrains IDEs, with deep IDE integration for project-aware suggestions.

Llama 3.2 added open 11B and 90B vision models plus compact 1B and 3B text models for edge and on-device use.

Qwen2.5 expanded the open family with stronger coding, mathematics, structured output, instruction following, and multilingual support across 29 languages.

First OpenAI o-series reasoning model that spends more time thinking before answering, with strong gains on coding, math, and science benchmarks.

MiniMax's first general text model with long context and competitive Chinese-English bilingual performance.

Grok-2 advanced chat, coding, and reasoning capabilities and introduced image generation in the Grok product.

Mistral Large 2 expanded context to 128K tokens and improved multilingual reasoning, code generation, and function calling.

Meta's first frontier-scale open-weights Llama with 405B parameters, 128K context, multilingual support, and tool use, rivaling closed models on many benchmarks.

Gemma 2 in 9B and 27B sizes with grouped-query attention and stronger efficiency at inference than Gemma 1.

First Claude 3.5 model: outperforms Claude 3 Opus on many benchmarks at Sonnet-tier speed and cost, with Artifacts for editable code and documents in the Claude app.

Qwen2 added models up to 72B parameters, support for 27 additional languages, stronger code and math performance, and up to 128K context.

Updated Gemma 1 checkpoints with improved chat quality and stability versus the February 2024 release.

Gemini 1.5 Flash delivered native multimodal reasoning and a 1M-token context window in a model optimized for low latency and high-volume tasks.

OpenAI's flagship omni model reasoning across audio, vision, and text in real time, rolled out in ChatGPT (including free tier) with improved latency versus GPT-4.

Llama 3 launched open 8B and 70B instruction models with substantially stronger reasoning, coding, and instruction following.

Command R+ scaled Cohere's RAG, multilingual, and multi-step tool-use capabilities for more demanding enterprise workloads.

Grok-1.5 improved mathematical and coding reasoning and expanded context to 128K tokens.

First Haiku model in the Claude 3 family: fast, cost-efficient, and strong on vision and multilingual tasks compared with Claude 2.1.

Command R introduced a 128K enterprise model optimized for retrieval-augmented generation with citations, multilingual tasks, and tool use.

Anthropic's most capable Claude 3 model at launch, setting new benchmarks for complex reasoning and long-form tasks on claude.ai and the Claude API.

Claude 3 Sonnet launched as the balanced member of Anthropic's first natively multimodal Claude family, with 200K context and image understanding.

Mistral Large debuted as Mistral's flagship multilingual model for complex reasoning, coding, JSON output, and function calling.

First Gemma open models (2B and 7B) released under the Gemma license for responsible commercial use.

Google's Gemini 1.5 Pro with dramatically expanded context (up to 1M tokens) and stronger multimodal understanding across long documents and video.

Google's largest Gemini 1.0 model (Ultra 1.0), launched via Gemini Advanced with leading multimodal understanding across MMLU-style benchmarks.

Qwen1.5 open-sourced base and chat models across a broad size range with 32K context, stronger multilingual alignment, and standard Transformers support.

Google made Gemini 1.0 Pro available to developers through Google AI Studio and Vertex AI as the balanced tier of its first natively multimodal family.

Mixtral 8x7B introduced an Apache 2.0 sparse mixture-of-experts model with 32K context, multilingual support, and strong code performance.

Claude 2.1 doubled context to 200K tokens, reduced false statements, and added tool use and system prompts for enterprise workloads.

GPT-4 Turbo expanded context to 128K tokens, added an April 2023 knowledge cutoff, and lowered API prices at OpenAI DevDay.

SpaceXAI introduced Grok-1 as its first large language model, later publishing the 314B-parameter mixture-of-experts weights and architecture.

Mistral 7B debuted a compact 7.3B-parameter open model using grouped-query and sliding-window attention under Apache 2.0.

Alibaba introduced the Qwen family with open 7B base and chat checkpoints supporting Chinese and English, coding, and tool-oriented prompting.

Llama 2 brought openly available pretrained and chat models up to 70B parameters with commercial use permitted under Meta's community license.

Anthropic's second-generation assistant improved coding, reasoning, and safety while expanding the context window to 100K tokens.

OpenAI's first large multimodal GPT-4 model, with strong performance on professional and academic benchmarks and broad availability in ChatGPT Plus and via API waitlist.

Meta released the original LLaMA research models in sizes up to 65B parameters, establishing the foundation for the open Llama family.