# Nanbeige4.2-3B vs Qwen3.5-122B-A10B (slim)

> Qwen3.5-122B-A10B scores 63.1 (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.

- Full: https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-122b-a10b.md (~9,650 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-122b-a10b.json · canonical https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-122b-a10b
- 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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Qwen3.5-122B-A10B scores 63.1 (B) on agent readiness against Nanbeige4.2-3B's 61 (C), and leads in 0 of 4 scored categories. Nanbeige4.2-3B leads on reach, agent interface and documentation and upkeep. 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
- Qwen3.5-122B-A10B: B 63.1, rank #25 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-5-122b-a10b.min.md
- 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 80; Agent interface, 85 against 70; Documentation and upkeep, 72 against 34.
- Qwen3.5-122B-A10B, good for Agents with a 128 GB unified-memory machine or two large GPUs that want a capable vision-language model with a plain licence.

| Category | Nanbeige4.2-3B | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 80 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 70 |
| Documentation and upkeep (10%) | 72 | 34 |

| Fact (where they differ) | Nanbeige4.2-3B | Qwen3.5-122B-A10B |
| --- | --- | --- |
| Vendor | Nanbeige LLM Lab (BOSS Zhipin) | Alibaba (Qwen team) |
| Licence | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) | Apache-2.0 |
| Last release | 2026-09-11 | 2026-02-24 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, Nanbeige4.2-3B +38: 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…); Qwen3.5-122B-A10B 34 (The card covers five of the seven items and misses limitations and a cut-off (14).)
- Agent interface, Nanbeige4.2-3B +15: 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…); Qwen3.5-122B-A10B 70 (The template ships in the repository (20) and renders several tool calls per turn for a model trained for tool use (20).)
- Reach, Nanbeige4.2-3B +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.); Qwen3.5-122B-A10B 80 (Memory earns 10 of 30, since Alibaba's GPTQ 4-bit build is 78.9 GB, about 95 GB with a fifth added, which fits our reference machine but no smaller band.)