# LongCat-2.5 vs Swift 1.5 Qwen3.8-Flash-Next (slim)

> Swift 1.5 Qwen3.8-Flash-Next scores 54.2 (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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Swift 1.5 Qwen3.8-Flash-Next scores 54.2 (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
- Swift 1.5 Qwen3.8-Flash-Next: C 54.2, rank #132 of 160 open-weight models · https://www.anchorterminal.com/tools/swift-1-5-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 60; Documentation and upkeep, 46 against 40.
- Swift 1.5 Qwen3.8-Flash-Next, good for Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work. Ahead on Reach, 65 against 35.

| Category | LongCat-2.5 | Swift 1.5 Qwen3.8-Flash-Next |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 35 | 65 |
| Risk (20%) | 60 | 45 |
| Agent interface (10%) | 75 | 60 |
| Documentation and upkeep (10%) | 46 | 40 |

| Fact (where they differ) | LongCat-2.5 | Swift 1.5 Qwen3.8-Flash-Next |
| --- | --- | --- |
| Vendor | Meituan (LongCat) | UkisAI |
| Licence | MIT | Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue |
| Last release | 2026-11-10 | 2026-09-24 |
| Terms last updated | not read yet | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 1.8/5 (4) |

Why the edge:
- Reach, Swift 1.5 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.); Swift 1.5 Qwen3.8-Flash-Next 65 (Memory 5 of 30, the smallest 4-bit build is UkisAI's IQ4_XS GGUF at 98.6 GB with the vision projector, 118.3 GB with a fifth, above the reference machine's GPU…)
- 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.); Swift 1.5 Qwen3.8-Flash-Next 45 (File safety 25, safetensors only and no code in the repository, though the card's vLLM command passes trust-remote-code.)
- 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.); Swift 1.5 Qwen3.8-Flash-Next 60 (Chat template 20, the base's Jinja file.)
- Documentation and upkeep, LongCat-2.5 +6: LongCat-2.5 46 (Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card.); Swift 1.5 Qwen3.8-Flash-Next 40 (Model card 5 of 20, intended use and context only.)