4,182 models

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cerebras/zai-glm-4.7 128K context $2.25/M input $2.75/M output

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ollama/llama2:7b 4.096K context Input not listed Output not listed

No provider description is available for this model yet.

bedrock/sa-east-1/deepseek.v3.2 163.84K context $0.74/M input $2.22/M output

The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...

mistralai/ministral-14b-2512 262.144K context $0.2/M input $0.2/M output

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...

z-ai/glm-4.5 131.072K context $0.6/M input $2.2/M output

Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...

inclusionai/ling-2.6-1t 262.144K context $0.075/M input $0.625/M output
Open weights

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meta-llama/CodeLlama-34b-hf Not documented context Input not listed Output not listed

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ollama/llama2:70b 4.096K context Input not listed Output not listed

GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...

openai/gpt-5.4-nano:batch 400K context $0.1/M input $0.625/M output

NVIDIA Nemotron 3 Nano 30B A3B is a small language MoE model with highest compute efficiency and accuracy for developers to build specialized agentic AI systems. The model is fully...

nvidia/nemotron-3-nano-30b-a3b:free 256K context Free input Free output
Open weights

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meta-llama/CodeLlama-34b-Python-hf Not documented context Input not listed Output not listed
Open weights

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meta-llama/CodeLlama-34b-Instruct-hf Not documented context Input not listed Output not listed

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...

anthropic/claude-opus-4.6 1M context $5/M input $25/M output

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...

openai/gpt-oss-20b:free 131.072K context Free input Free output

The simplest way to get free inference. openrouter/free is a router that selects free models at random from the models available on OpenRouter. The router smartly filters for models that...

openrouter/free 200K context Free input Free output

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...

qwen/qwen3-next-80b-a3b-instruct:free 262.144K context Free input Free output

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

qwen/qwen3-coder-next 262.144K context $0.12/M input $0.8/M output

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

deepseek/deepseek-chat-v3.1 163.84K context $0.25/M input $0.95/M output

Grok Build 0.1 is SpaceXAI’s fast coding model trained specifically for agentic software engineering workflows. It supports text and image inputs with text output, and is optimized for interactive coding...

x-ai/grok-build-0.1 256K context $1/M input $2/M output

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...

meta-llama/llama-3.2-3b-instruct 131.072K context $0.05/M input $0.33/M output
Open weights

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meta-llama/CodeLlama-70b-hf Not documented context Input not listed Output not listed
Open weights

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meta-llama/CodeLlama-70b-Python-hf Not documented context Input not listed Output not listed

Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...

thinkingmachines/inkling:free 1.04858M context Free input Free output
Open weights

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meta-llama/CodeLlama-70b-Instruct-hf Not documented context Input not listed Output not listed
Open weights

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meta-llama/Llama-2-7b Not documented context Input not listed Output not listed

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...

minimax/minimax-m2.5 200K context $0.27/M input $1.08/M output
Open weights

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meta-llama/Llama-2-13b Not documented context Input not listed Output not listed

Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...

thinkingmachines/inkling-small:batch 524.288K context $0.5/M input $1.2/M output

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

qwen/qwen3.5-397b-a17b 262.144K context $0.55/M input $3.5/M output

Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...

qwen/qwen3-vl-30b-a3b-thinking 131.072K context $0.2/M input $2.4/M output

Hy-MT2-7B is a 7B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.

tencent/hy-mt2-7b 8.192K context $0.074/M input $0.295/M output