# Ling-3.1-flash-1019 vs Qwen3-Coder-30B-A3B-Instruct (slim)

> Qwen3-Coder-30B-A3B-Instruct and Ling-3.1-flash-1019 score within a point of each other for open-weight models you run yourself, 55.7 and 54.8 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct.md (~11,100 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-coder-30b-a3b-instruct
- 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-Coder-30B-A3B-Instruct and Ling-3.1-flash-1019 score within a point of each other on agent readiness, 55.7 (C) and 54.8 (C). 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-Coder-30B-A3B-Instruct: C 55.7, rank #119 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct.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 31.
- Qwen3-Coder-30B-A3B-Instruct, good for Coding agents and local coding tools that want an open model on one 24 GB GPU or a 32 GB Mac, with a plain licence. Ahead on Reach, 90 against 60; Risk, 55 against 45; Agent interface, 75 against 60.

| Category | Ling-3.1-flash-1019 | Qwen3-Coder-30B-A3B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 90 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 75 |
| Documentation and upkeep (10%) | 56 | 31 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Qwen3-Coder-30B-A3B-Instruct |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2025-12-03 |
| Agent reviews | none | 2.8/5 (4) |

Why the edge:
- Reach, Qwen3-Coder-30B-A3B-Instruct +30: 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-Coder-30B-A3B-Instruct 90 (Memory 25 of 30, LM Studio's MLX 4-bit build is 17.2 GB and Ollama's 4-bit build 19 GB, 21 to 23 GB with a fifth added, which fits 24 GB.)
- Documentation and upkeep, Ling-3.1-flash-1019 +25: 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-Coder-30B-A3B-Instruct 31 (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-Coder-30B-A3B-Instruct +15: 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-Coder-30B-A3B-Instruct 75 (Chat template 20, chat_template.jinja in the repository.)
- Risk, Qwen3-Coder-30B-A3B-Instruct +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-Coder-30B-A3B-Instruct 55 (File safety 25, safetensors weights, and the shipped parser script runs neither to load the model nor to build prompts.)