# Olmo 3 7B Think vs OTel-2.0-LLM-31B-IT (slim)

> OTel-2.0-LLM-31B-IT scores 56.8 (C) to Olmo 3 7B Think's 52.3 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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- 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 Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on reach and risk. Both do open-weight models you run yourself.

- Olmo 3 7B Think: D 52.3, rank #139 of 160 open-weight models · https://www.anchorterminal.com/tools/olmo-3-7b-think.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
- Olmo 3 7B Think, good for Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand Ahead on Reach, 75 against 50; Risk, 75 against 55.
- 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 Agent interface, 60 against 35; Documentation and upkeep, 74 against 52.

| Category | Olmo 3 7B Think | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 75 | 50 |
| Risk (20%) | 75 | 55 |
| Agent interface (10%) | 35 | 60 |
| Documentation and upkeep (10%) | 52 | 74 |

| Fact (where they differ) | Olmo 3 7B Think | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | Ai2 (Allen Institute for AI) | AT&T (Open Telco AI) |
| Licence | Apache-2.0, with Ai2's Responsible Use Guidelines named on the card | Apache-2.0 |
| Last release | 2026-06-25 | 2026-11-01 |
| Terms last updated | 2024-09-25 | no document linked |
| Privacy policy last updated | 2025-02-19 | no document linked |
| Customer content may train models | yes | 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 | not found in the text | not read yet |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, Olmo 3 7B Think +25: Olmo 3 7B Think 75 (Memory earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library).); 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…)
- Agent interface, OTel-2.0-LLM-31B-IT +25: Olmo 3 7B Think 35 (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.)
- Documentation and upkeep, OTel-2.0-LLM-31B-IT +22: Olmo 3 7B Think 52 (The model card earns 17, missing only the context length.); 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.)
- Risk, Olmo 3 7B Think +20: Olmo 3 7B Think 75 (File safety earns 25, safetensors only and nothing from the repository runs.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)