# DeepSeek-V4-Flash-0731 vs Nanbeige4.2-3B (slim)

> DeepSeek-V4-Flash-0731 and Nanbeige4.2-3B score within a point of each other for open-weight models you run yourself, 61.9 and 61 out of 100. 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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DeepSeek-V4-Flash-0731 and Nanbeige4.2-3B score within a point of each other on agent readiness, 61.9 (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-Flash-0731: C 61.9, rank #33 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.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-Flash-0731, good for Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context
- 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 70; Risk, 55 against 50; Agent interface, 85 against 75; Documentation and upkeep, 72 against 38.

| Category | DeepSeek-V4-Flash-0731 | Nanbeige4.2-3B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 70 | 85 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 75 | 85 |
| Documentation and upkeep (10%) | 38 | 72 |

| Fact (where they differ) | DeepSeek-V4-Flash-0731 | 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 | 2026-07-31 | 2026-09-11 |
| Agent reviews | 2.5/5 (4) | none |

Why the edge:
- Documentation and upkeep, Nanbeige4.2-3B +34: DeepSeek-V4-Flash-0731 38 (Model card 8, the card and the DSpark card it names give architecture, parameters and context, with intended use, limitations, languages and cut-off missing.); 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…)
- Reach, Nanbeige4.2-3B +15: DeepSeek-V4-Flash-0731 70 (Memory 5, because the smallest build of 4-bit or better from a runtime's own library is LM Studio's MXFP4 GGUF at 156.4 GB, which with a fifth added needs 187.7…); 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.)
- Agent interface, Nanbeige4.2-3B +10: DeepSeek-V4-Flash-0731 75 (Chat template 10, there is no Jinja template and the format is given as Python to run.); 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-Flash-0731 50 (File safety 15, safetensors only, less 10 because prompts are built by running DeepSeek's encoding_dsv4.py from the repository and the card's serving commands p…); Nanbeige4.2-3B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)