# DeepSeek V4.1 Flash vs Nanbeige4.2-3B (slim)

> DeepSeek V4.1 Flash and Nanbeige4.2-3B score within a point of each other for open-weight models you run yourself, 61.5 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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DeepSeek V4.1 Flash and Nanbeige4.2-3B score within a point of each other on agent readiness, 61.5 (C) and 61 (C). Nanbeige4.2-3B leads on reach, risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.

- DeepSeek V4.1 Flash: C 61.5, rank #35 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-1-flash.min.md
- Nanbeige4.2-3B: C 61, rank #78 of 160 open-weight models · https://www.anchorterminal.com/tools/nanbeige-4-2-3b.min.md
- DeepSeek V4.1 Flash, good for Teams with a multi-GPU server who want DeepSeek's agent model under MIT, with the hosted API as a fallback.
- Nanbeige4.2-3B, good for Local agents that need tool calling and a long context on a laptop or a small GPU Ahead on Reach, 85 against 60; Risk, 55 against 50; Agent interface, 85 against 75; Documentation and upkeep, 72 against 48.

| Category | DeepSeek V4.1 Flash | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 48 | 72 |

| Fact (where they differ) | DeepSeek V4.1 Flash | Nanbeige4.2-3B |
| --- | --- | --- |
| Vendor | DeepSeek | Nanbeige LLM Lab (BOSS Zhipin) |
| Licence | MIT | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Last release | 2026-10-17 | 2026-09-11 |
| Agent reviews | 2.8/5 (4) | none |

Why the edge:
- Reach, Nanbeige4.2-3B +25: DeepSeek V4.1 Flash 60 (Memory scores nothing, because the only build is DeepSeek's own at 510.3 GB, about 612 GB with the fifth added, and nobody's runtime library holds a smaller one…); 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.)
- Documentation and upkeep, Nanbeige4.2-3B +24: DeepSeek V4.1 Flash 48 (The cards cover architecture, parameters and context but not intended use, limitations, languages or a cut-off, so 8. Training data is a general description wit…); 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…)
- Agent interface, Nanbeige4.2-3B +10: DeepSeek V4.1 Flash 75 (There's no Jinja template in the 17 October repository, only code to run, so the template line gets 10. DeepSeek documents the DSML tool format both ways and sh…); 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…)
- Risk, Nanbeige4.2-3B +5: DeepSeek V4.1 Flash 50 (The weights are safetensors only, but 10 comes off because the card's way to build prompts is running encoding.py from the repository, since there's no Jinja te…); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)