# GLM-4.7-Flash vs Qwen3-VL-2B-Instruct (slim)

> GLM-4.7-Flash scores 63 (B) to Qwen3-VL-2B-Instruct's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-2b-instruct.md (~6,250 tokens) · this version ~430 tokens · JSON https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-2b-instruct.json · canonical https://www.anchorterminal.com/compare/glm-4-7-flash-vs-qwen3-vl-2b-instruct
- 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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GLM-4.7-Flash scores 63 (B) on agent readiness against Qwen3-VL-2B-Instruct's 61 (C), and leads in 1 of 4 scored categories. Qwen3-VL-2B-Instruct leads on reach. 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
- Qwen3-VL-2B-Instruct: C 61, rank #45 of 100 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct.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 Agent interface, 85 against 60.
- Qwen3-VL-2B-Instruct, good for An agent on a laptop or small edge device that needs a local model to read images, documents and video in about 2 GB Ahead on Reach, 95 against 80.

| Category | GLM-4.7-Flash | Qwen3-VL-2B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 80 | 95 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 28 | 31 |

| Fact (where they differ) | GLM-4.7-Flash | Qwen3-VL-2B-Instruct |
| --- | --- | --- |
| Vendor | Z.ai (Zhipu AI) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-01-29 | 2025-11-01 |