Loading the catalogue…
Loading the catalogue…
Anthropic's low-latency multimodal model featuring a 1,000,000-token context window and configurable reasoning effort.
OpenAI's closed-weight reasoning model with a 1,050,000-token context window, mandatory configurable reasoning effort and native hosted tools, sitting between GPT-6 Sol and the GPT-6 Astra flagship.
Anthropic's closed-weight Sonnet-class reasoning model with a 1M-token context window, always-on adaptive thinking, and configurable effort levels.
Xiaomi's open-weight 1.02T-parameter omnimodal reasoning model with a 1M-token context, accepting text, image, video and audio input and returning text.
OpenAI's flagship closed-weight reasoning model with a 1.05M-token context window and mandatory reasoning on every request.
Google's reasoning-tuned Flash-tier model for fast coding, agentic, and multi-step reasoning tasks with a million-token multimodal context window.
Anthropic's frontier reasoning model with a 1M-token context window, always-on adaptive reasoning, and native text-and-image input.
Anthropic's frontier reasoning model with a 1M-token context, adjustable reasoning effort, and multimodal input for code, research, and long-document work.
Google's fast, cost-focused Gemini 3.5 model with a million-token context window, mandatory configurable reasoning, and multimodal text, image, audio, and video input.
Google's reasoning-tuned Flash model: multimodal input, a million-token-plus context window, and always-on chain-of-thought for agentic, long-horizon tasks.
Moonshot AI's open-weights, always-reasoning 2.8T MoE flagship with a 1M-token context, native tool use, and multimodal input.
OpenAI's flagship GPT-5.6 reasoning model for agentic coding, cybersecurity, and long-horizon analysis, with a 1.05M-token context window.
OpenAI's balanced GPT-5.6 model, offering a 1.05M-token context window and configurable reasoning effort for mid-complexity coding and document tasks.
xAI's proprietary reasoning model with a 500,000-token context window, mandatory configurable reasoning effort, and text and image input.
Anthropic's adaptive-reasoning Sonnet-class model with a 1M-token context window, strong Design Arena coding and UI results, and always-on reasoning selectable from low to max effort.
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.
xAI's agentic coding model: a 256K-context, tool-calling assistant with mandatory step-by-step reasoning, built for multi-step debugging and MCP orchestration.
Anthropic's frontier reasoning model with a 1M-token context window, built for complex agentic workflows, graduate-level analysis, and long-context tasks.
Google's fast, cost-optimised multimodal Gemini model with a million-token context window, built for high-throughput text, image, audio, video, and file input.
xAI's reasoning model with a 1M-token context window and configurable reasoning effort, on by default.
OpenAI's long-context instruct model, built for complex multi-step reasoning, long-document analysis, and tool orchestration across a 1M+ token context window.
Anthropic's frontier-tier closed-weight instruct model with a one-million-token context window, built for complex, long-horizon reasoning and coding rather than real-time interaction.
OpenAI's efficient GPT-5.4 mini instruct model, built for coding and agentic workloads with optional reasoning depth and a 400K-token multimodal context window.
xAI's multi-agent orchestration model: parallel sub-agent debate synthesized into one answer, built for deliberate reasoning over speed.
OpenAI's configurable chain-of-thought reasoning model with a 1M-token context window and native text, image, and file input.
Google's frontier reasoning model with mandatory chain-of-thought inference, a 1M-token context window, and full multimodal input for long-horizon, complex tasks.
A hybrid-reasoning Claude model from Anthropic with a 1M-token context window, selectable reasoning effort, and tool calling for coding, research, and agentic work.
One of Anthropic's Claude Opus 4 models — a one-million-token context window, optional adaptive thinking, and native document understanding for reasoning-heavy and agentic work.
Google's multimodal Flash model with a 1M+ token context and opt-in reasoning effort, built for fast Inference on complex, mixed-media tasks.
Mistral AI's open-weight flagship: a 675B-parameter (41B active) Granular MoE model with native vision input, function calling, and a 262,144-token context window, built for long-document and multimodal workflows.
Anthropic's frontier Claude Opus 4.5: a proprietary, text-and-image model 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, optional extended thinking, vision input, and strong safety benchmarks.
Anthropic's instruct-tuned Claude Sonnet 4.5 — built for agentic coding, computer-use, and long-context reasoning via the Claude API.
OpenAI's compact GPT-5 variant with tunable reasoning effort, a 400K-token context window, and multimodal input for interactive document and image tasks.
OpenAI's fastest, lightest GPT-5 tier for high-volume classification, summarisation, and short completions — 400K context, vision and file input, mandatory reasoning traces.
Mistral AI's code-specialised API model for fill-in-the-middle completion, code correction and test generation, with a 256K-token context window.
Google's fastest, lowest-cost Gemini 2.5 model — a multimodal instruct model with a 1M-token context window, built for realtime, high-throughput Inference.
Google's closed-weight, reasoning-tuned flagship with a 1M-token context window, multimodal input, and native tool calling.
Google DeepMind's efficiency-tier multimodal model with a 1M-token context window, optional chain-of-thought thinking, and native text, image, audio, video, and file input.