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Chutes 的网站图标

Chutes

浏览以下提供商提供的模型: Chutes (服务条款)

7 个模型

OpenRouter 处理的 token 数

  • qwen 的网站图标
    Qwen: Qwen3.8 27BQwen3.8 27B

    Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be enabled or disabled.

    作者: qwen2026年8月14日262K 上下文US$0.039/M 输入 tokenUS$1.25/M 输出 token
  • deepseek 的网站图标
    DeepSeek: DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

    DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows. This is the GA release of DeepSeek V4 Flash.

    作者: deepseek2026年7月31日1.05M 上下文US$0.44/M 输入 tokenUS$1.32/M 输出 token
  • moonshotai 的网站图标
    MoonshotAI: Kimi K3Kimi K3

    Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

    作者: moonshotai2026年7月16日1.05M 上下文US$1.85/M 输入 tokenUS$9.50/M 输出 token
  • qwen 的网站图标
    Qwen: Qwen3.6 27BQwen3.6 27B

    Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs — and supports a 262,144-token context window. The model is designed for agentic coding and reasoning tasks, with particular strength in repository-level code comprehension, front-end development workflows, and multi-step problem solving. It includes a built-in thinking mode for extended reasoning and preserves thinking context across conversation history. Qwen3.6 27B supports 201 languages and dialects and is released under the Apache 2.0 license.

    作者: qwen2026年4月27日262K 上下文US$0.25/M 输入 tokenUS$2/M 输出 token
  • moonshotai 的网站图标
    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.

    作者: moonshotai2026年4月20日262K 上下文US$0.39/M 输入 tokenUS$1.80/M 输出 token
  • z-ai 的网站图标
    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.

    作者: z-ai2026年4月7日203K 上下文US$0.90/M 输入 tokenUS$2.90/M 输出 token
  • google 的网站图标
    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.

    作者: google2026年4月2日262K 上下文US$0.12/M 输入 tokenUS$0.37/M 输出 token