# Laguna M.1 vs OTel-2.0-LLM-31B-IT (slim)

> OTel-2.0-LLM-31B-IT and Laguna M.1 score within a point of each other for open-weight models you run yourself, 56.8 and 56.7 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it.md (~9,400 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/laguna-m-1-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/laguna-m-1-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 and Laguna M.1 score within a point of each other on agent readiness, 56.8 (C) and 56.7 (C). Laguna M.1 leads on reach and agent interface. Both do open-weight models you run yourself.

- Laguna M.1: C 56.7, rank #112 of 160 open-weight models · https://www.anchorterminal.com/tools/laguna-m-1.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
- Laguna M.1, good for Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0. Ahead on Reach, 70 against 50; Agent interface, 85 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 Documentation and upkeep, 74 against 36.

| Category | Laguna M.1 | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 50 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 36 | 74 |

| Fact (where they differ) | Laguna M.1 | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Poolside | AT&T (Open Telco AI) |
| Last release | 2026-07-14 | 2026-11-01 |
| Terms last updated | 2026-07-21 | no document linked |
| Privacy policy last updated | 2026-07-21 | no document linked |
| Customer content may train models | yes, with an opt-out | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | yes | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +38: Laguna M.1 36 (Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't.); 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, Laguna M.1 +25: Laguna M.1 85 (Chat template 20, a Jinja file 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.)
- Reach, Laguna M.1 +20: Laguna M.1 70 (Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine.); 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…)