# DeepSeek V4.1 Flash vs Olmo 3 7B Think (slim)

> DeepSeek V4.1 Flash scores 59 (C) to Olmo 3 7B Think's 52.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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DeepSeek V4.1 Flash scores 59 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 5 scored categories. Olmo 3 7B Think leads on reach and risk. Both do open-weight models you run yourself.

- DeepSeek V4.1 Flash: C 59, rank #63 of 100 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-1-flash.min.md
- Olmo 3 7B Think: D 52.3, rank #86 of 100 open-weight models · https://www.anchorterminal.com/tools/olmo-3-7b-think.min.md
- DeepSeek V4.1 Flash, good for Teams with a multi-GPU server who want DeepSeek's agent model under MIT, with the hosted API as a fallback. Ahead on Capability, 69 against 28; Agent interface, 75 against 35.
- Olmo 3 7B Think, good for Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand Ahead on Reach, 75 against 50; Risk, 75 against 50.

| Category | DeepSeek V4.1 Flash | Olmo 3 7B Think |
| --- | --- | --- |
| Capability (35%) | 69 | 28 |
| Reach (25%) | 50 | 75 |
| Risk (20%) | 50 | 75 |
| Agent interface (10%) | 75 | 35 |
| Documentation and upkeep (10%) | 48 | 52 |

| Fact (where they differ) | DeepSeek V4.1 Flash | Olmo 3 7B Think |
| --- | --- | --- |
| Vendor | DeepSeek | Ai2 (Allen Institute for AI) |
| Licence | MIT | Apache-2.0, with Ai2's Responsible Use Guidelines named on the card |
| Last release | 2026-10-17 | 2026-06-25 |
| Terms last updated | no document linked |  |
| Privacy policy last updated | no document linked |  |