# Cola2 vs Qwen3.5-9B (slim)

> Qwen3.5-9B scores 60.5 (C) to Cola2's 33.9 (F) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-9b.md (~8,750 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-9b.json · canonical https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-9b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Qwen3.5-9B scores 60.5 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Cola2: F 33.9, rank #160 of 160 open-weight models · https://www.anchorterminal.com/tools/cola2.min.md
- Qwen3.5-9B: C 60.5, rank #87 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-9b.min.md
- Cola2, good for Researchers working on latent or diffusion language models who want a checkpoint to study Ahead on Documentation and upkeep, 58 against 34.
- Qwen3.5-9B, good for Agents that want a small multimodal tool-calling model on a laptop or a 16 GB GPU, under a plain licence Ahead on Reach, 85 against 25; Risk, 55 against 40; Agent interface, 70 against 20.

| Category | Cola2 | Qwen3.5-9B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 25 | 85 |
| Risk (20%) | 40 | 55 |
| Agent interface (10%) | 20 | 70 |
| Documentation and upkeep (10%) | 58 | 34 |

| Fact (where they differ) | Cola2 | Qwen3.5-9B |
| --- | --- | --- |
| Vendor | ByteDance (Seed) | Alibaba (Qwen team) |
| Licence | None stated for the weights (the code is Apache 2.0) | Apache-2.0 |
| Last release | 2026-11-06 | 2026-03-02 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Reach, Qwen3.5-9B +60: Cola2 25 (Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB.); Qwen3.5-9B 85 (Memory 30, Qwen publishes no quantised 9B, so the smallest 4-bit build from a runtime's own library is Ollama's qwen3.5:9b at 6.6 GB, about 7.9 GB with the fift…)
- Agent interface, Qwen3.5-9B +50: Cola2 20 (Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer.); Qwen3.5-9B 70 (Chat template 20, a Jinja file in the repository.)
- Documentation and upkeep, Cola2 +24: Cola2 58 (Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model c…); Qwen3.5-9B 34 (Model card 14, it covers intended use, architecture, parameters, context and 201 languages but gives no limitations and no knowledge cut-off.)
- Risk, Qwen3.5-9B +15: Cola2 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Qwen3.5-9B 55 (File safety 25, safetensors only and nothing from the repository runs on load or to build prompts.)