# Ling-3.1-flash-1019 vs Qwen3.5-0.8B (slim)

> Ling-3.1-flash-1019 scores 54.8 (C) to Qwen3.5-0.8B's 46.7 (D) 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-qwen3-5-0-8b.md (~9,550 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-0-8b.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-5-0-8b
- 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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Ling-3.1-flash-1019 scores 54.8 (C) on agent readiness against Qwen3.5-0.8B's 46.7 (D), and leads in 1 of 4 scored categories. Qwen3.5-0.8B leads on reach and risk. 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
- Qwen3.5-0.8B: D 46.7, rank #156 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-0-8b.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 37.
- Qwen3.5-0.8B, good for Builders who want a near-free local helper or fine-tuning base for narrow tasks on a phone-class device, laptop or CPU Ahead on Reach, 80 against 60; Risk, 55 against 45.

| Category | Ling-3.1-flash-1019 | Qwen3.5-0.8B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 80 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 56 | 37 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Qwen3.5-0.8B |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2026-03-02 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Qwen3.5-0.8B +20: 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.); Qwen3.5-0.8B 80 (Memory earns the full 30, since LM Studio's Q4_K_M build with its projector is 0.73 GB (0.88 GB with the fifth added) and Ollama's Q8_0 build was 1.0 GB, both f…)
- Documentation and upkeep, Ling-3.1-flash-1019 +19: 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…); Qwen3.5-0.8B 37 (The card covers six of the seven items, missing only a cut-off (17), because it states the intended uses and warns about thinking loops.)
- Risk, Qwen3.5-0.8B +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…); Qwen3.5-0.8B 55 (Safetensors only with no remote code gives file safety its 25, and files in the Qwen organisation the publisher's GitHub links to, each with a hash on the Hub…)