# Ling-3.1-flash-1019 vs Qwen3.5-9B (slim)

> Qwen3.5-9B scores 60.5 (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-qwen3-5-9b.md (~10,050 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-9b.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Qwen3.5-9B scores 60.5 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in 3 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
- Qwen3.5-9B: C 60.5, rank #87 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-9b.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 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 60; Risk, 55 against 45; Agent interface, 70 against 60.

| Category | Ling-3.1-flash-1019 | Qwen3.5-9B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 56 | 34 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Qwen3.5-9B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2026-03-02 |
| Agent reviews | none | 2.5/5 (4) |

Why the edge:
- Reach, Qwen3.5-9B +25: 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.); Qwen3.5-9B 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…)
- Documentation and upkeep, Ling-3.1-flash-1019 +22: 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…); Qwen3.5-9B 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 +10: Ling-3.1-flash-1019 45 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the…); Qwen3.5-9B 55 (File safety 25, safetensors only and nothing from the repository runs on load or to build prompts.)
- Agent interface, Qwen3.5-9B +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.); Qwen3.5-9B 70 (Chat template 20, a Jinja file in the repository.)