# LFM2.5-2.6B vs OTel-2.0-LLM-31B-IT (slim)

> OTel-2.0-LLM-31B-IT scores 56.8 (C) to LFM2.5-2.6B's 50.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-otel-2-0-llm-31b-it.md (~9,850 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/lfm2-5-2-6b-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 LFM2.5-2.6B's 50.3 (D), and leads in 2 of 4 scored categories. LFM2.5-2.6B leads on reach and agent interface. Both do open-weight models you run yourself.

- LFM2.5-2.6B: D 50.3, rank #146 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm2-5-2-6b.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
- LFM2.5-2.6B, good for Agents that want a small local helper for tool calls, extraction and RAG on a laptop, phone or CPU, at organisations under the licence's revenue threshold Ahead on Reach, 90 against 50; Agent interface, 75 against 60.
- 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 50; Documentation and upkeep, 74 against 57.

| Category | LFM2.5-2.6B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 50 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 75 | 60 |
| Documentation and upkeep (10%) | 57 | 74 |

| Fact (where they differ) | LFM2.5-2.6B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Liquid AI | AT&T (Open Telco AI) |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-11-01 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Reach, LFM2.5-2.6B +40: LFM2.5-2.6B 90 (Memory earns the full 30, since Liquid's own 4-bit GGUF is 1.59 GB and fits 8 GB with room to spare.); 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…)
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +17: LFM2.5-2.6B 57 (The model card earns 17, with everything but a knowledge cut-off.); 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.)
- Agent interface, LFM2.5-2.6B +15: LFM2.5-2.6B 75 (The chat template earns 20 for chat_template.jinja in the repository.); OTel-2.0-LLM-31B-IT 60 (Chat template 20, chat_template.jinja in the repository, 19,300 characters, the publisher's own.)
- Risk, OTel-2.0-LLM-31B-IT +5: LFM2.5-2.6B 50 (File safety earns 25, safetensors and GGUF only, and nothing from the repository runs to load it or build prompts.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)