# Nemotron 3 Nano Omni 30B A3B Reasoning vs OTel-2.0-LLM-31B-IT (slim)

> Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) to OTel-2.0-LLM-31B-IT's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-otel-2-0-llm-31b-it.md (~11,650 tokens) · this version ~830 tokens · JSON https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-otel-2-0-llm-31b-it.json · canonical https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-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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Nemotron 3 Nano Omni 30B A3B Reasoning scores 61.2 (C) on agent readiness against OTel-2.0-LLM-31B-IT's 56.8 (C), and leads in 3 of 4 scored categories. Both do open-weight models you run yourself.

- Nemotron 3 Nano Omni 30B A3B Reasoning: C 61.2, rank #36 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.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
- Nemotron 3 Nano Omni 30B A3B Reasoning, good for Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools Ahead on Reach, 85 against 50; Risk, 60 against 55; Agent interface, 90 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

| Category | Nemotron 3 Nano Omni 30B A3B Reasoning | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 50 |
| Risk (20%) | 60 | 55 |
| Agent interface (10%) | 90 | 60 |
| Documentation and upkeep (10%) | 70 | 74 |

| Fact (where they differ) | Nemotron 3 Nano Omni 30B A3B Reasoning | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Vendor | NVIDIA | AT&T (Open Telco AI) |
| Licence | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) | Apache-2.0 |
| Last release | 2026-08-24 | 2026-11-01 |
| Terms last updated | no date given | no document linked |
| Customer content may train models | not found in the text | 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 | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | 3/5 (4) | none |

Why the edge:
- Reach, Nemotron 3 Nano Omni 30B A3B Reasoning +35: Nemotron 3 Nano Omni 30B A3B Reasoning 85 (Memory earns 20 because the smallest 4-bit builds, Ollama's NVFP4 at 21 GB and NVIDIA's NVFP4 at 22.4 GB, need about 25 to 27 GB with the fifth added, which fit…); 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, Nemotron 3 Nano Omni 30B A3B Reasoning +30: Nemotron 3 Nano Omni 30B A3B Reasoning 90 (A Jinja template ships in the repository (20).); OTel-2.0-LLM-31B-IT 60 (Chat template 20, chat_template.jinja in the repository, 19,300 characters, the publisher's own.)
- Risk, Nemotron 3 Nano Omni 30B A3B Reasoning +5: Nemotron 3 Nano Omni 30B A3B Reasoning 60 (File safety gets 15, safetensors only but loaded with trust_remote_code.); OTel-2.0-LLM-31B-IT 55 (File safety 25, safetensors only, with no .bin, .pt or .pth files and no Python files.)