# DeepSeek-V3.2 vs Kimi K3 (slim)

> Kimi K3 scores 62.4 (B) to DeepSeek-V3.2's 58.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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Kimi K3 scores 62.4 (B) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 4 of 5 scored categories. DeepSeek-V3.2 leads on reach. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #65 of 100 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- Kimi K3: B 62.4, rank #29 of 100 open-weight models · https://www.anchorterminal.com/tools/kimi-k3.min.md
- DeepSeek-V3.2, good for Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider Ahead on Reach, 60 against 50.
- Kimi K3, good for Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work Ahead on Capability, 75 against 69; Risk, 65 against 50; Agent interface, 65 against 60; Documentation and upkeep, 41 against 34.

| Category | DeepSeek-V3.2 | Kimi K3 |
| --- | --- | --- |
| Capability (35%) | 69 | 75 |
| Reach (25%) | 60 | 50 |
| Risk (20%) | 50 | 65 |
| Agent interface (10%) | 60 | 65 |
| Documentation and upkeep (10%) | 34 | 41 |

| Fact (where they differ) | DeepSeek-V3.2 | Kimi K3 |
| --- | --- | --- |
| Vendor | DeepSeek | Moonshot AI |
| Licence | MIT | Kimi K3 License (modified MIT) |
| Last release | 2025-12-01 | 2026-09-02 |