# Ling-3.1-flash-1019 vs OTel-2.0-LLM-31B-IT (slim)

> OTel-2.0-LLM-31B-IT scores 56.8 (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-otel-2-0-llm-31b-it.md (~10,200 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-otel-2-0-llm-31b-it
- 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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OTel-2.0-LLM-31B-IT scores 56.8 (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 reach. 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
- OTel-2.0-LLM-31B-IT: C 56.8, rank #111 of 160 open-weight models · https://www.anchorterminal.com/tools/otel-2-0-llm-31b-it.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 50.
- OTel-2.0-LLM-31B-IT, good for Telecoms teams that want an open model for standards questions and RAG on their own hardware Ahead on Risk, 55 against 45; Documentation and upkeep, 74 against 56.

| Category | Ling-3.1-flash-1019 | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 50 |
| Risk (20%) | 45 | 55 |
| Agent interface (10%) | 60 | 60 |
| Documentation and upkeep (10%) | 56 | 74 |

| Fact (where they differ) | Ling-3.1-flash-1019 | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | inclusionAI (Ant Group) | AT&T (Open Telco AI) |
| Licence | MIT | Apache-2.0 |
| Last release | 2026-11-04 | 2026-11-01 |

Why the edge:
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +18: 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…); OTel-2.0-LLM-31B-IT 74 (Model card 14, Intended use, a long limitations section, the architecture and training method, the parameters (31B) and the language (English) are on the card.)
- Reach, Ling-3.1-flash-1019 +10: 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.); OTel-2.0-LLM-31B-IT 50 (Memory 10, the publisher's only build is the BF16 safetensors, 62.55 GB for the 15 shards the index names, and 62.55 GB × 1.2 = 75.1 GB, above 64 GB and inside…)
- Risk, OTel-2.0-LLM-31B-IT +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…); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)