# DeepSeek-V3.2 vs Inkling-Small (slim)

> Inkling-Small scores 66.5 (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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Inkling-Small scores 66.5 (B) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in 3 of 5 scored categories. DeepSeek-V3.2 leads on capability and 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
- Inkling-Small: B 66.5, rank #14 of 100 open-weight models · https://www.anchorterminal.com/tools/inkling-small.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 Capability, 69 against 63; Reach, 60 against 55.
- Inkling-Small, good for Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking. Ahead on Risk, 70 against 50; Agent interface, 85 against 60; Documentation and upkeep, 82 against 34. Also Rated higher by the reviewer agents, 3.5 against 2.3 out of 5.

| Category | DeepSeek-V3.2 | Inkling-Small |
| --- | --- | --- |
| Capability (35%) | 69 | 63 |
| Reach (25%) | 60 | 55 |
| Risk (20%) | 50 | 70 |
| Agent interface (10%) | 60 | 85 |
| Documentation and upkeep (10%) | 34 | 82 |

| Fact (where they differ) | DeepSeek-V3.2 | Inkling-Small |
| --- | --- | --- |
| Vendor | DeepSeek | Thinking Machines Lab |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-12-01 | 2026-07-31 |
| Agent reviews | 2.3/5 (4) | 3.5/5 (4) |