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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.
xAI's closed-weight, reasoning-tuned model for long-running agentic coding and research, with a 500K-token context window and configurable reasoning depth.
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 configurable chain-of-thought for agentic, long-horizon tasks.
OpenAI's fast, cost-efficient GPT-5.6 tier for high-volume chat, classification, and lightweight agentic tasks with a 1.05M-token context window.
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xAI's closed-weight reasoning model (xAI's flagship at its July 2026 launch, since superseded) with a 500,000-token context window, mandatory chain-of-thought, and strong coding benchmarks.
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 DeepMind's Flash-tier multimodal model with a 1M-token context window and always-on, effort-adjustable reasoning for text, image, video, audio, and file inputs.
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.
Google's multimodal embedding model, unifying text, image, audio, video, and document inputs into a single adjustable-dimension vector space.
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.
Google DeepMind's open-weight, multimodal Mixture-of-Experts model with a 262K-token context window, tuned for interactive-latency, moderate-complexity tasks.
Google DeepMind's open-weights 30.7B dense multimodal model with a 256K-token context window and optional chain-of-thought thinking, instruction-tuned for long-context and multimodal tasks.
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 non-reasoning Grok 4.20 snapshot: 1M-token context, vision input, tool calling, and structured outputs, with mid-pack Artificial Analysis Intelligence Index scores.
xAI's chain-of-thought reasoning model in the Grok 4.20 generation, built for deliberate multi-step inference across text and image input.
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 a 1M-token context window, mandatory chain-of-thought inference, 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.
OpenAI's agentic coding model in the GPT-5 family, built for terminal and IDE workflows with a 400K-token context window and native tool orchestration.
Google's multimodal Flash model with a 1M+ token context and opt-in reasoning effort, built for fast Inference on complex, mixed-media tasks.
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 code-specialised GPT-5 variant for multi-step, tool-using coding workflows.
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.
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.
Google's preview text-to-speech model for expressive, single- and multi-speaker audio generation from text prompts.
OpenAI's compact, instruction-tuned multimodal model for high-throughput, realtime-latency Inference on medium-complexity tasks.
OpenAI's 2024 multimodal flagship for fast, complex text-and-vision tasks with tool calling, structured outputs, and a 128K context window.
OpenAI's closed-weight GPT-4 Turbo brings a 128K-token context window and text+image input to complex, long-context tasks at interactive latency.
OpenAI's flagship closed-weight text embedding model, producing configurable-dimension vectors (up to 3,072-d) for search and retrieval workloads with an 8,191-token input window.
OpenAI's cost-efficient third-generation text embedding model for semantic search and retrieval, producing configurable 1,536-dimension vectors.
OpenAI's instruction-tuned completion model for the legacy /v1/completions endpoint — a fast, interactive-latency option for short-form text generation and simple prompt-completion workflows without chat structure or tool calling.
OpenAI's original GPT-4: a proprietary, text-only instruct model for professional writing, reasoning, and basic tool-calling workflows, with an 8k-token context window and a 2021 training cutoff.
OpenAI's GPT-3.5 Turbo is a fast, text-only chat model built for high-volume, simple conversational tasks via the Chat Completions API, with tool calling and JSON mode support.
Stav review in progress.
Stav review in progress.
Stav review in progress.
Stav review in progress.
Stav review in progress.
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