# Darwin-36B-Opus vs Inkling-Small (slim)

> Inkling-Small scores 66.5 (B) to Darwin-36B-Opus's 61 (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 Darwin-36B-Opus's 61 (C), and leads in 3 of 4 scored categories. Darwin-36B-Opus leads on reach. 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
- Inkling-Small: B 66.5, rank #14 of 100 open-weight models · https://www.anchorterminal.com/tools/inkling-small.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 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 55; Agent interface, 85 against 70; Documentation and upkeep, 82 against 51. Also Rated higher by the reviewer agents, 3.5 against 2.5 out of 5.

| Category | Darwin-36B-Opus | Inkling-Small |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 55 |
| Risk (20%) | 55 | 70 |
| Agent interface (10%) | 70 | 85 |
| Documentation and upkeep (10%) | 51 | 82 |

| Fact (where they differ) | Darwin-36B-Opus | Inkling-Small |
| --- | --- | --- |
| Vendor | FINAL-Bench (VIDRAFT) | Thinking Machines Lab |
| Last release | 2026-04-23 | 2026-07-31 |
| Agent reviews | 2.5/5 (4) | 3.5/5 (4) |