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OpenCode Data: Real-world AI model usage, cache ratios, and costs

OpenCode released data on real-world AI model usage, cache ratios, and costs, showing DeepSeek's v4-flash leading with 8.2T tokens, followed by DeepSeek v4-pro and Zhipu's glm-5.2. The data reveals shifting model adoption and cost implications for developers.

read1 min views1 publishedJul 8, 2026
OpenCode Data: Real-world AI model usage, cache ratios, and costs
Image: source

Model Data See which models are winning real usage, how the mix is shifting, and what that means for cost.

Top Models. Usage of models across OpenCode Go.

[Top Models.](#top-models)

[04](/data/minimax/minimax-m3)

minimax-m3 960B

MiniMax-61%

05 mimo-v2.5 827B

Xiaomi-4%

[06](/data/moonshot/kimi-k2-7-code)

**kimi-k2.7-code** 391B

Moonshot-17%

[07](/data/xiaomi/mimo-v2-5-pro)

**mimo-v2.5-pro** 273B

Xiaomi-5%

08 qwen3.7-plus 247B

Qwen+15%

09 kimi-k2.6 118B

Moonshot-15%

10 glm-5.1 59B

Zhipu-20%

11 minimax-m2.7 54B

MiniMax-14%

12 qwen3.7-max 54B

Qwen-4%

13 qwen3.6-plus 39B

Qwen-2%

14 kimi-k2.5 6B

Moonshot-19%

15 glm-5 5B

Zhipu-14%

16 minimax-m2.5 5B

MiniMax-7%

17 qwen3.5-plus 2B

Qwen-45%

18 hy3-preview 0B

Tencent-58%

[01](/data/deepseek/deepseek-v4-flash)

**deepseek-v4-flash** 8.2T

DeepSeek-20%

[02](/data/deepseek/deepseek-v4-pro)

**deepseek-v4-pro** 2.8T

DeepSeek-27%

03 glm-5.2 1.3T

Zhipu-17%

04 minimax-m3 960B

MiniMax-61%

05 mimo-v2.5 827B

Xiaomi-4%

[06](/data/moonshot/kimi-k2-7-code)

**kimi-k2.7-code** 391B

Moonshot-17%

[07](/data/xiaomi/mimo-v2-5-pro)

**mimo-v2.5-pro** 273B

Xiaomi-5%

08 qwen3.7-plus 247B

Qwen+15%

09 kimi-k2.6 118B

Moonshot-15%

10 glm-5.1 59B

Zhipu-20%

11 minimax-m2.7 54B

MiniMax-14%

12 qwen3.7-max 54B

Qwen-4%

13 qwen3.6-plus 39B

Qwen-2%

14 kimi-k2.5 6B

Moonshot-19%

15 glm-5 5B

Zhipu-14%

16 minimax-m2.5 5B

MiniMax-7%

17 qwen3.5-plus 2B

Qwen-45%

18 hy3-preview 0B

Tencent-58%

LEARN MORE TOP MODELS Unique Users. Daily unique OpenCode Go users by model.

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