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Friendli 的网站图标

Friendli

浏览以下提供商提供的模型: Friendli (服务条款)

5 个模型

OpenRouter 处理的 token 数

  • z-ai 的网站图标
    Z.ai: GLM 5.3 FlashGLM 5.3 Flash

    GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

    作者: z-ai2026年8月26日1.05M 上下文US$0.15/M 输入 tokenUS$0.50/M 输出 token
  • z-ai 的网站图标
    Z.ai: GLM 5.3GLM 5.3
    10% off

    GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency. Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

    作者: z-ai2026年8月18日1.05M 上下文US$1.26/M 输入 tokenUS$3.96/M 输出 token
  • z-ai 的网站图标
    Z.ai: GLM 5.2GLM 5.2

    GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is particularly strong at coding and tool use across long-running tasks, able to maintain engineering context and follow standards consistently through a full development workflow, from requirements to multi-platform deployment, in a single task.

    作者: z-ai2026年6月16日1.05M 上下文US$1.40/M 输入 tokenUS$4.40/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$1.40/M 输入 tokenUS$4.40/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$0.14/M 输入 tokenUS$0.40/M 输出 token