# LongCat-2.5 vs Qwen3.8-Flash-Next (slim)

> Qwen3.8-Flash-Next scores 61.8 (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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Qwen3.8-Flash-Next scores 61.8 (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
- Qwen3.8-Flash-Next: C 61.8, rank #34 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-8-flash-next.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 45; Agent interface, 75 against 70; Documentation and upkeep, 46 against 36.
- Qwen3.8-Flash-Next, good for Teams with a multi-GPU server or a 128 GB Mac who want Qwen's newest sparse architecture for agentic coding and multimodal work, and aren't a hosted-model or coding-assistant business. Ahead on Reach, 65 against 35.

| Category | LongCat-2.5 | Qwen3.8-Flash-Next |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 65 |
| Risk (20%) | 60 | 45 |
| Agent interface (10%) | 75 | 70 |
| Documentation and upkeep (10%) | 46 | 36 |

| Fact (where they differ) | LongCat-2.5 | Qwen3.8-Flash-Next |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | Alibaba (Qwen team) |
| Licence | MIT | Qwen Community License 1.0 (custom, not an OSI licence). Free of charge, the model name shown in products above 100M monthly users or US$20M monthly revenue, and a separate licence from Qwen before commercial use by a Model as a Service or AI Work Assistant business |
| Last release | 2026-11-10 | 2026-08-31 |
| Terms last updated | not read yet | no document linked |
| Agent reviews | none | 2/5 (4) |

Why the edge:
- Reach, Qwen3.8-Flash-Next +30: 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.); Qwen3.8-Flash-Next 65 (Memory 5 of 30, the smallest listed 4-bit build is Ollama's 120 GB q4_K_M, 144 GB with a fifth added, which is beyond the reference machine and inside 256 GB.)
- Risk, LongCat-2.5 +15: LongCat-2.5 60 (File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository.); Qwen3.8-Flash-Next 45 (File safety 25, safetensors only and nothing from the repository runs to load it or build prompts.)
- Documentation and upkeep, LongCat-2.5 +10: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Qwen3.8-Flash-Next 36 (Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, languages and a knowledge cut-off aren't.)
- Agent interface, LongCat-2.5 +5: LongCat-2.5 75 (Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json.); Qwen3.8-Flash-Next 70 (Chat template 20, a Jinja file in the repository.)