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Cursor

An AI code editor built on VS Code.

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Set up Cursor

The examples use MoonshotAI: Kimi K3, a live model on llm.buzz. Any model name from the Models page works.

  1. Create a key in the llm.buzz console under Keys, and keep it in the LLM_BUZZ_KEY environment variable.

  2. In Cursor Settings, Models, paste your key into the OpenAI API Key field, turn on Override OpenAI Base URL and enter llm.buzz's base URL.

    OpenAI API Key
    Your llm.buzz key
    Override OpenAI Base URL
    https://api.llm.buzz/api/v1

  3. Add the model's name as a custom model and pick it in the chat's model picker.

    Model name
    moonshotai/kimi-k3

  4. Cursor sends these requests through its own servers, and only chat uses your key: Tab completion stays on Cursor's own models.

Usage on llm.buzz

Weekly tokens from requests that name this app.

Rankings
Tokens last week
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Rank last week
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among apps on llm.buzz
vs prior week
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Tokens, 12 weeks
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Tokens by week

Usage is published weekly, once at least 5 organizations use a model. The current week closes Monday, Nov 2, 2026, 00:00 UTC.

Top models

No model's usage is published for Cursor yet.

A model or app appears only when at least 5 organizations used it that week and no single one sent more than 80% of its tokens.

Popular models for coding agents

Live models that call tools, the most used and most widely served first.

All tool-calling models
1M context10% off
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Output
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GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks.

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Providers
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Qwen: Qwen3.8 27Bby Qwen

Qwen3.8 27B is an open-weight dense vision-language model from Qwen.

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Z.ai: GLM 5.3 Flashby Z.ai

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks.

Providers
4
Input
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OpenAI: gpt-oss-120bby OpenAI

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and…

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Point Cursor at llm.buzzOne key for every model here; each request pays the price of the provider that answered it.
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