Models

OpenAI's compact open-weight model with 20 billion parameters. Released under Apache 2.0 license, designed for efficient deployment on consumer hardware while maintaining strong coding and reasoning capabilities.

Anthropic's latest and most advanced model with state-of-the-art reasoning, coding, and analysis capabilities. Features improved tool use, extended thinking, and enhanced safety alignment.

OpenAI's first open-weight large model with 120 billion parameters. Released under Apache 2.0 license, offering strong performance on reasoning and coding tasks while being fully self-hostable.

xAI's latest and most intelligent model with strong agentic tool calling, minimal hallucinations, and configurable reasoning. Supports 1M token context window with competitive pricing.

NVIDIA's open hybrid Mamba-Transformer MoE model with 120B total parameters (12B active). Features 1M token context window and excels at agentic reasoning, coding, planning, and tool calling.

OpenAI's frontier reasoning model combining advances in coding, reasoning, and agentic workflows. Features 1.1M token context window and strong performance on complex multi-step problems.

Google's latest flagship multimodal model with state-of-the-art performance on reasoning, coding, and multimodal understanding. Features native tool use, grounding, and million-token context window.

OpenAI's premium tier model with extended reasoning capabilities, higher accuracy on complex tasks, and priority access. Optimized for professional and enterprise workloads requiring maximum quality.

Compact multilingual language model from Cohere For AI with 3.35B parameters, optimized for efficient and balanced multilingual representation across 70+ languages including many lower-resourced ones. Designed for edge deployment without cloud dependency. Trained on 64 NVIDIA H100 GPUs with specialized regional variants available (Global, Earth, Fire).

xAI's multi-agent capable model with 2M token context window. Available in reasoning, non-reasoning, and multi-agent variants for diverse enterprise workloads.

xAI's latest model with real-time information access, strong reasoning capabilities, and competitive performance on coding and analysis tasks. Features improved tool use and multimodal understanding.

Anthropic's balanced model offering strong performance at lower cost and latency than Opus. Excellent for everyday coding, analysis, and content generation tasks with good reasoning capabilities.

Anthropic's most capable model in the Claude 4 family, excelling at complex analysis, extended reasoning, scientific research, and advanced code generation. Features significantly improved accuracy and reduced hallucinations.

xAI's fast and cost-effective model with 2M token context window. Offers both reasoning and non-reasoning modes at significantly lower pricing than flagship models.

Anthropic's fastest model with near-frontier intelligence. Optimized for high-throughput, low-latency applications requiring quick responses at minimal cost. Supports extended thinking.

Anthropic's previous-generation balanced model with strong coding and analysis capabilities. Offers excellent price-performance ratio for production workloads requiring reliable quality.

Google's cost-effective model optimized for high throughput tasks. Balances speed and intelligence with strong multimodal capabilities and 1M token context window.

Google's high-capability reasoning model with adaptive thinking for complex agentic and multimodal challenges. Features 1M token context window and strong performance on coding and scientific tasks.

NVIDIA's compact 9B parameter model trained from scratch for both reasoning and non-reasoning tasks. Generates reasoning traces before final responses. Efficient for edge and on-device deployment.

OpenAI's fifth-generation flagship model with significant improvements in reasoning, multimodal understanding, and code generation. Features enhanced instruction following and expanded context window.

Meta's efficient MoE model with 17B active parameters (109B total, 16 experts). Supports up to 10M token context — the longest of any production model. Strong performance on reasoning and multilingual tasks.

Meta's quality-focused MoE model with 17B active parameters (400B total, 128 experts). Targets quality-critical tasks with benchmark scores competitive with GPT-4o and Gemini 2.5 Pro.

Google's largest open-weight model in the Gemma 3 family with 27 billion parameters. Supports multimodal inputs including text and images with a 128K context window. Delivers strong performance across reasoning, code generation, and vision tasks, competitive with larger proprietary models.

Google's mid-size open-weight model with 12 billion parameters from the Gemma 3 family. Supports multimodal inputs including text and images with a 128K context window. Strong performance on reasoning and code generation tasks at moderate compute cost.