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

> Ling-3.1-flash-1019 scores 54.8 (C) to Qwen3-Omni-30B-A3B-Instruct's 41.8 (E) 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-omni-30b-a3b-instruct.md (~11,050 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-omni-30b-a3b-instruct.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-qwen3-omni-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
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Ling-3.1-flash-1019 scores 54.8 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in 2 of 4 scored categories. Qwen3-Omni-30B-A3B-Instruct leads on 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-Omni-30B-A3B-Instruct: E 41.8, rank #158 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-omni-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 Reach, 60 against 55; Documentation and upkeep, 56 against 26.
- Qwen3-Omni-30B-A3B-Instruct, good for Agents on a machine with about 96 GB to spare that need one local model to hear, see and answer by voice Ahead on Risk, 55 against 45.

| Category | Ling-3.1-flash-1019 | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 55 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 56 | 26 |

| Fact (where they differ) | Ling-3.1-flash-1019 | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | Alibaba (Qwen team) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2025-09-22 |
| Agent reviews | none | 2/5 (4) |

Why the edge:
- Documentation and upkeep, Ling-3.1-flash-1019 +30: 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-Omni-30B-A3B-Instruct 26 (Model card 11, intended use, architecture, parameters and languages are there, limitations, context and a cut-off aren't.)
- Risk, Qwen3-Omni-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-Omni-30B-A3B-Instruct 55 (File safety 25, safetensors only and no code in the repository, so the cookbook's trust_remote_code flag runs nothing.)
- Reach, Ling-3.1-flash-1019 +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-Omni-30B-A3B-Instruct 55 (Memory earns 10, because the only build is the 70.5 GB BF16 checkpoint, about 85 GB with a fifth added, which fits only the reference machine's band.)