Guide

OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning...

Fast o-series model for compact reasoning, coding, and tool use

Deliberate o-series reasoner for hard math, coding, and multi-step analysis

Deliberate o-series reasoner for hard math, coding, and multi-step analysis

Fast o-series model for compact reasoning, coding, and tool use

Deliberate o-series reasoner for hard math, coding, and multi-step analysis

Fast o-series model for compact reasoning, coding, and tool use

Qwen instruction model for multilingual chat, reasoning, and tool use

Fast o-series model for compact reasoning, coding, and tool use

Deliberate o-series reasoner for hard math, coding, and multi-step analysis

Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE,...

Embedding model for semantic search, retrieval, clustering, and ranking pipelines

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and...

GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...

GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million...

Llemma 7B is a language model for mathematics. It was initialized with Code Llama 7B weights, and trained on the Proof-Pile-2 for 200B tokens. Llemma models are particularly strong at...

A finetuned 7 billion parameters Code LLaMA - Instruct model to generate Solidity smart contract using 4-bit QLoRA finetuning provided by PEFT library.

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

Affordable GPT-4.1 lane for fast coding help and structured extraction

Long-lived GPT workhorse for coding, instruction following, and production apps

Affordable GPT-4.1 lane for fast coding help and structured extraction

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

Long-lived GPT workhorse for coding, instruction following, and production apps

Affordable GPT-4.1 lane for fast coding help and structured extraction

Long-lived GPT workhorse for coding, instruction following, and production apps

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

Long-lived GPT workhorse for coding, instruction following, and production apps

Affordable GPT-4.1 lane for fast coding help and structured extraction

Grok 3 Mini is a lightweight, smaller thinking model. Unlike traditional models that generate answers immediately, Grok 3 Mini thinks before responding. It’s ideal for reasoning-heavy tasks that don’t demand...

Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in...

Llama-3.1-Nemotron-Ultra-253B-v1 is a large language model (LLM) optimized for advanced reasoning, human-interactive chat, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta’s Llama-3.1-405B-Instruct, it has been significantly customized using Neural...

Mistral vision-language model for image understanding and multimodal chat

Mistral vision-language model for image understanding and multimodal chat

Mistral vision-language model for image understanding and multimodal chat

Open Llama instruction model for multilingual chat, reasoning, and coding

Open multimodal Llama model for strong reasoning and fast responses

Open multimodal Llama model for long-context analysis and efficient agents

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

Open multimodal Llama model for long-context analysis and efficient agents

Llama 4 Maverick 17B from Groq - text, image input, 131,072 token context

Llama Guard 4 12B from Groq - text, image input, 131,072 token context

Llama-4-Scout-17B-16E-Instruct from Synthetic - text, image input, 328,000 token context

Llama-4-Maverick-17B-128E-Instruct-FP8 from Synthetic - text, image input, 524,000 token context

Open multimodal Llama for strong reasoning with efficient everyday serving

Open Llama with long-context vision for efficient multimodal agents

Open multimodal Llama for strong reasoning with efficient everyday serving