# DeepSeek-V4-Flash-0731 vs Olmo 3 7B Think (slim)

> DeepSeek-V4-Flash-0731 scores 62.4 (B) 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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- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-21
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DeepSeek-V4-Flash-0731 scores 62.4 (B) 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, risk and documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek-V4-Flash-0731: B 62.4, rank #28 of 100 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.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-Flash-0731, good for Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context Ahead on Capability, 66 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 70; Risk, 75 against 50; Documentation and upkeep, 52 against 43.

| Category | DeepSeek-V4-Flash-0731 | Olmo 3 7B Think |
| --- | --- | --- |
| Capability (35%) | 66 | 28 |
| Reach (25%) | 70 | 75 |
| Risk (20%) | 50 | 75 |
| Agent interface (10%) | 75 | 35 |
| Documentation and upkeep (10%) | 43 | 52 |

| Fact (where they differ) | DeepSeek-V4-Flash-0731 | 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 | 2026-07-31 | 2026-06-25 |
| Terms last updated | no document linked |  |
| Privacy policy last updated | no document linked |  |
| Agent reviews | 2.5/5 (4) | 2.8/5 (4) |