# Ling-3.1-flash-1019 vs Qwen3.8-Flash-Next (slim)

> Qwen3.8-Flash-Next scores 61.8 (C) to Ling-3.1-flash-1019's 54.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next.md (~10,250 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-8-flash-next
- 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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Qwen3.8-Flash-Next scores 61.8 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 2 of 4 scored categories. Ling-3.1-flash-1019 leads on documentation and upkeep. Both do open-weight models you run yourself.

- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.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
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding Ahead on Documentation and upkeep, 56 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 60; Agent interface, 70 against 60.

| Category | Ling-3.1-flash-1019 | Qwen3.8-Flash-Next |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 65 |
| Risk (20%) | 45 | 45 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 56 | 36 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Qwen3.8-Flash-Next |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | 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 | 2026-11-04 | 2026-08-31 |
| Agent reviews | none | 2/5 (4) |

Why the edge:
- Documentation and upkeep, Ling-3.1-flash-1019 +20: Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…); 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, Qwen3.8-Flash-Next +10: Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.); Qwen3.8-Flash-Next 70 (Chat template 20, a Jinja file in the repository.)
- Reach, Qwen3.8-Flash-Next +5: Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.); 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.)