# LongCat-2.5 vs Qwen3-VL-2B-Instruct (slim)

> Qwen3-VL-2B-Instruct scores 61 (C) to LongCat-2.5's 50.5 (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: 2026-11-10
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Qwen3-VL-2B-Instruct scores 61 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 1 of 4 scored categories. LongCat-2.5 leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- LongCat-2.5: D 50.5, rank #145 of 160 open-weight models · https://www.anchorterminal.com/tools/longcat-2-5.min.md
- Qwen3-VL-2B-Instruct: C 61, rank #52 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct.min.md
- LongCat-2.5, good for Operators with NPU clusters, and anyone tracking what the open flagships can do Ahead on Risk, 60 against 55; Agent interface, 75 against 60; Documentation and upkeep, 46 against 31.
- 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 35.

| Category | LongCat-2.5 | Qwen3-VL-2B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 95 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 75 | 60 |
| Documentation and upkeep (10%) | 46 | 31 |

| Fact (where they differ) | LongCat-2.5 | Qwen3-VL-2B-Instruct |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-10 | 2025-11-01 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Qwen3-VL-2B-Instruct +60: LongCat-2.5 35 (Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB.); Qwen3-VL-2B-Instruct 95 (Alibaba's own Q4_K_M GGUF with its vision file is 1.56 GB, so with a fifth added it needs about 1.9 GB and fits well within 16 GB (30).)
- Agent interface, LongCat-2.5 +15: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); Qwen3-VL-2B-Instruct 60 (A Jinja chat template in the repository (20).)
- Documentation and upkeep, LongCat-2.5 +15: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Qwen3-VL-2B-Instruct 31 (The card misses limitations, languages and a cut-off (11).)
- Risk, LongCat-2.5 +5: LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); Qwen3-VL-2B-Instruct 55 (Safetensors and GGUF only and no code in the repositories, so the FP8 card's trust_remote_code flag runs nothing (25).)