# Nanbeige4.2-3B vs Nemotron 3 Nano 30B A3B (slim)

> Nemotron 3 Nano 30B A3B scores 67.6 (B) to Nanbeige4.2-3B's 61 (C) 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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Nemotron 3 Nano 30B A3B scores 67.6 (B) on agent readiness against Nanbeige4.2-3B's 61 (C), and leads in every scored category. Both do open-weight models you run yourself.

- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.min.md
- Nemotron 3 Nano 30B A3B: B 67.6, rank #12 of 160 open-weight models · https://www.anchorterminal.com/tools/nemotron-3-nano-30b-a3b.min.md
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU
- Nemotron 3 Nano 30B A3B, good for Agents with a 24 to 32 GB GPU or Mac that want a quick tool-calling and reasoning cousin with very long context. Ahead on Reach, 90 against 85; Risk, 60 against 55; Agent interface, 90 against 85; Documentation and upkeep, 80 against 72.

| Category | Nanbeige4.2-3B | Nemotron 3 Nano 30B A3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 90 |
| Risk (20%) | 55 | 60 |
| Agent interface (10%) | 85 | 90 |
| Documentation and upkeep (10%) | 72 | 80 |

| Fact (where they differ) | Nanbeige4.2-3B | Nemotron 3 Nano 30B A3B |
| --- | --- | --- |
| Vendor | Nanbeige LLM Lab (BOSS Zhipin) | NVIDIA |
| Licence | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) | NVIDIA Nemotron Open Model License (custom, Apache-style, commercial use allowed, not an OSI licence) |
| Last release | 2026-09-11 | 2026-08-24 |
| Terms last updated | no document linked | 2025-12-15 |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Agent reviews | none | 3.3/5 (4) |

Why the edge:
- Documentation and upkeep, Nemotron 3 Nano 30B A3B +8: Nanbeige4.2-3B 72 (Model card 17, Intended use, limitations, the architecture, the parameters (3B outside the embeddings), the context and the languages (in the metadata) are on t…); Nemotron 3 Nano 30B A3B 80 (The model card earns 20, with all seven items on the card and its subcards.)
- Reach, Nemotron 3 Nano 30B A3B +5: Nanbeige4.2-3B 85 (Memory 30, the smallest build from Nanbeige is the FP8 repository (the 8-bit GPTQ one is the same size), 5.19 GB, and 5.19 GB × 1.2 = 6.2 GB, within 16 GB.); Nemotron 3 Nano 30B A3B 90 (Memory earns 25 because the smallest 4-bit build is Ollama's NVFP4 MLX build at 18 GB, 21.6 GB with the fifth added, and NVIDIA's own NVFP4 build lands in the s…)
- Risk, Nemotron 3 Nano 30B A3B +5: Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Nemotron 3 Nano 30B A3B 60 (File safety earns 15, safetensors only but with the documented serving path passing trust-remote-code and loading a reasoning parser file from the repository.)
- Agent interface, Nemotron 3 Nano 30B A3B +5: Nanbeige4.2-3B 85 (Chat template 20, A Jinja chat template in tokenizer_config.json (7,961 characters), with enable_thinking, preserve_thinking, tools and tool_call_format switche…); Nemotron 3 Nano 30B A3B 90 (The chat template earns 20 as a Jinja file in the repository.)