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Favicon for Crusoe

Crusoe

Browse models provided by Crusoe (Terms of Service)

7 models

Tokens processed on OpenRouter

  • Favicon for moonshotai
    MoonshotAI: Kimi K2.6Kimi K2.6

    Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

    by moonshotaiApr 20, 2026262K context$0.70/M input tokens$3.50/M output tokens
  • Favicon for z-ai
    Z.ai: GLM 5.1GLM 5.1

    GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on a single task for more than 8 hours, autonomously planning, executing, and improving itself throughout the process, ultimately delivering complete, engineering-grade results.

    by z-aiApr 7, 2026203K context$1.20/M input tokens$4.40/M output tokens
  • Favicon for google
    Google: Gemma 4 31BGemma 4 31B

    Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.

    by googleApr 2, 2026262K context$0.14/M input tokens$0.40/M output tokens
  • Favicon for nvidia
    NVIDIA: Nemotron 3 Nano 30B A3BNemotron 3 Nano 30B A3B

    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 open with open-weights, datasets and recipes so developers can easily customize, optimize, and deploy the model on their infrastructure for maximum privacy and security.

    by nvidiaDec 14, 2025256K context$0.05/M input tokens$0.20/M output tokens
  • Favicon for qwen
    Qwen: Qwen3 235B A22B Instruct 2507Qwen3 235B A22B Instruct 2507

    Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following, logical reasoning, math, code, and tool usage. The model supports a native 262K context length and does not implement "thinking mode" (<think> blocks). Compared to its base variant, this version delivers significant gains in knowledge coverage, long-context reasoning, coding benchmarks, and alignment with open-ended tasks. It is particularly strong on multilingual understanding, math reasoning (e.g., AIME, HMMT), and alignment evaluations like Arena-Hard and WritingBench.

    by qwenJul 21, 2025262K context$0.22/M input tokens$0.80/M output tokens
  • Favicon for deepseek
    DeepSeek: DeepSeek V3 0324DeepSeek V3 0324

    DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the DeepSeek V3 model and performs really well on a variety of tasks.

    by deepseekMar 24, 2025131K context$0.50/M input tokens$1.50/M output tokens
  • Favicon for meta-llama
    Meta: Llama 3.3 70B InstructLlama 3.3 70B Instruct

    The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks. Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. Model Card

    by meta-llamaDec 6, 2024131K context$0.25/M input tokens$0.75/M output tokens