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Anthropic's most agentic Sonnet-class model, featuring adaptive reasoning with selectable effort levels, a one-million-token context window, and strong coding and multi-step workflow performance.
Anthropic's frontier Mythos-class model with always-on adaptive reasoning and a one-million-token context window, built for deep code and research analysis rather than real-time chat.
Anthropic's most capable flagship model as of May 2026, built for complex agentic workflows, graduate-level reasoning, and long-context analysis — with a one-million-token context window and opt-in extended thinking.
Google DeepMind's frontier-tier multimodal Flash model with a 1M-token context window, optional extended thinking, and native support for text, image, video, audio, and file inputs — built for complex interactive workloads.
Google DeepMind's cost-optimised multimodal language model with a 1M-token context window, real-time latency, and optional extended thinking — built for high-throughput agentic and instruction-following workloads.
OpenAI's frontier agentic instruct model with a 1M+ token context window, built for complex multi-step reasoning, long-document analysis, and autonomous tool orchestration.
Alibaba's 27.8B open-weight multimodal reasoning model with near-frontier math, science, and code performance. Ships switchable thinking and non-thinking modes in a single checkpoint, across a 262,144-token context window.
Anthropic's iterative frontier flagship with a one-million-token context window, graduate-level reasoning (GPQA 0.914), enhanced vision, and optional extended thinking — built for complex long-horizon tasks.
Google DeepMind's instruction-tuned Mixture-of-Experts model with 25.2B total parameters and only 3.8B active per token, delivering high-tier reasoning and vision understanding across a 256K-token context window — available as open weights under Apache 2.0.
Google DeepMind's open-weights 30.7B dense multimodal model with a 256K-token context window, optional chain-of-thought thinking, and native function calling — instruction-tuned for complex, long-context, and multilingual tasks.
OpenAI's efficient GPT-5-generation model with a 400K context window, tool calling, structured output, and optional reasoning traces — optimised for high-throughput agentic and coding workloads.
OpenAI's frontier chain-of-thought reasoning model, combining GPT-5 and Codex capabilities in a single system with a 1M-token context window and native vision and document input.
Google's frontier reasoning model with a 1M-token context window, dynamic chain-of-thought thinking, and full multimodal input — built for complex, long-horizon inference tasks.
Anthropic's hybrid reasoning Sonnet model — frontier-grade GPQA scores, API-controlled extended thinking, and a 1M-token context window in beta, delivered at interactive speeds.
Anthropic's flagship reasoning model with a 1M-token context window (beta), adaptive thinking via /effort controls, and top benchmark results on Humanity's Last Exam, Terminal-Bench 2.0, BrowseComp, and GDPval-AA. Optimised for complex agentic and long-context workloads.
OpenAI's frontier agentic coding model combining top-tier software-engineering performance with broad professional reasoning, a 400K-token context window, and native support for reasoning traces and tool orchestration.
Google's frontier-tier Flash model with a 1M-token context, native multimodal inputs, and opt-in extended thinking — built for fast agentic workflows that need near-Pro reasoning.
Mistral AI's December 2025 open-weight flagship — a sparse MoE with 675B total / 41B active parameters, 256k context, native vision, and Apache 2.0 licence — built for complex instruction-following, agentic workflows, and multilingual deployments.
Anthropic's frontier Claude Opus 4.5, built for complex coding, research, and long-document reasoning with optional extended thinking.
Anthropic's fastest Claude 4 model — built for high-throughput agentic and coding workloads, with a 200K-token context window, extended thinking support, vision, and strong safety benchmarks.
Anthropic's instruct-tuned Claude Sonnet 4.5 for agentic coding, computer use, and long-context reasoning — now on a 200K context window and heading toward retirement.
OpenAI's first-generation GPT-5 coding variant, built for agentic workflows. Offers a 400,000-token context window, configurable reasoning effort, and full tool-calling support via the Responses API — designed for developers who need sustained, multi-step code reasoning at frontier quality.
OpenAI's compact GPT-5 variant — multimodal input, 400K context, optional extended thinking, and tool calling — tuned for interactive, medium-complexity workloads at a lighter weight than full GPT-5.
OpenAI's fastest GPT-5 tier — optimised for high-volume classification, summarisation, and short-completion tasks with a 400K context window, vision and file input, and optional reasoning traces.
Anthropic's agentic coding and research model with 74.5% SWE-bench Verified, 200K context, and extended thinking up to 64K tokens.
Google's fastest Gemini 2.5 variant — a multimodal, 1M-context instruct model built for realtime, high-throughput workloads with optional reasoning mode.
Google's flagship reasoning model with a one-million-token context window, adaptive chain-of-thought thinking, and native support for multimodal inputs, tool calling, web search grounding, and sandboxed code execution.
Google DeepMind's efficiency-tier multimodal model with a 1M-token context window, optional chain-of-thought thinking, and native support for text, image, audio, video, and file inputs.
OpenAI's compact multimodal model balancing capable instruction-following with realtime latency — the practical default for high-throughput text and vision workloads.
A 12B open-weights instruction model co-developed by Mistral AI and NVIDIA, featuring a 131k-token context window, the efficient Tekken tokenizer, native tool calling, and multilingual support across nine languages — available under Apache 2.0 for unrestricted self-hosted inference.
OpenAI's multimodal flagship with text and image input, 128K context, structured outputs, and interactive latency for complex instruction-following and vision tasks.
OpenAI's GPT-4 Turbo is a high-quality instruction-tuned model with a 128K context window, image input support, and full tool-calling capabilities — well-suited for complex, long-context, and multimodal tasks served at interactive latency.
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Anthropic's frontier Mythos-class model with always-on adaptive reasoning and a one-million-token context window, built for deep code and research analysis rather than real-time chat.