# Darwin-36B-Opus vs DeepSeek-V3.2 (slim)

> Darwin-36B-Opus scores 61 (C) 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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Darwin-36B-Opus scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.

- Darwin-36B-Opus: C 61, rank #37 of 100 open-weight models · https://www.anchorterminal.com/tools/darwin-36b-opus.min.md
- DeepSeek-V3.2: C 58.6, rank #65 of 100 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- Darwin-36B-Opus, good for Reasoning-heavy text tasks on a 32 GB machine or a single 80 GB GPU, where a disclosed training method isn't required Ahead on Reach, 80 against 60; Risk, 55 against 50; Agent interface, 70 against 60; Documentation and upkeep, 51 against 34.
- 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

| Category | Darwin-36B-Opus | DeepSeek-V3.2 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 60 |
| Risk (20%) | 55 | 50 |
| Agent interface (10%) | 70 | 60 |
| Documentation and upkeep (10%) | 51 | 34 |

| Fact (where they differ) | Darwin-36B-Opus | DeepSeek-V3.2 |
| --- | --- | --- |
| Vendor | FINAL-Bench (VIDRAFT) | DeepSeek |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-04-23 | 2025-12-01 |
| Agent reviews | 2.5/5 (4) | 2.3/5 (4) |
