# GLM-4.7-Flash vs Olmo 3 7B Think (slim)

> GLM-4.7-Flash scores 63 (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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GLM-4.7-Flash scores 63 (B) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on risk and documentation and upkeep. Both do open-weight models you run yourself.

- GLM-4.7-Flash: B 63, rank #26 of 100 open-weight models · https://www.anchorterminal.com/tools/glm-4-7-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
- GLM-4.7-Flash, good for Agents and developers who want a small, permissively licensed tool-calling model on one 24 to 32 GB GPU or Mac, in almost any runtime Ahead on Capability, 59 against 28; Reach, 80 against 75; Agent interface, 85 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 Risk, 75 against 55; Documentation and upkeep, 52 against 28.

| Category | GLM-4.7-Flash | Olmo 3 7B Think |
| --- | --- | --- |
| Capability (35%) | 59 | 28 |
| Reach (25%) | 80 | 75 |
| Risk (20%) | 55 | 75 |
| Agent interface (10%) | 85 | 35 |
| Documentation and upkeep (10%) | 28 | 52 |

| Fact (where they differ) | GLM-4.7-Flash | Olmo 3 7B Think |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Ai2 (Allen Institute for AI) |
| Licence | MIT | Apache-2.0, with Ai2's Responsible Use Guidelines named on the card |
| Last release | 2026-01-29 | 2026-06-25 |
| Terms last updated | no document linked |  |
| Privacy policy last updated | no document linked |  |