# Nanbeige4.2-3B vs Qwen3-VL-30B-A3B-Instruct (slim)

> Nanbeige4.2-3B scores 61 (C) to Qwen3-VL-30B-A3B-Instruct's 58 (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-vl-30b-a3b-instruct.md (~10,000 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-30b-a3b-instruct.json · canonical https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-30b-a3b-instruct
- 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
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Nanbeige4.2-3B scores 61 (C) on agent readiness against Qwen3-VL-30B-A3B-Instruct's 58 (C), and leads in 2 of 4 scored categories. Qwen3-VL-30B-A3B-Instruct leads on reach. 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-VL-30B-A3B-Instruct: C 58, rank #104 of 160 open-weight models · https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct.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 Agent interface, 85 against 60; Documentation and upkeep, 72 against 36.
- Qwen3-VL-30B-A3B-Instruct, good for An agent with 24 GB or more to spare that wants a local reader of images, documents and video with 262,144 tokens of context Ahead on Reach, 95 against 85.

| Category | Nanbeige4.2-3B | Qwen3-VL-30B-A3B-Instruct |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 85 | 95 |
| Risk (20%) | 55 | 55 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 72 | 36 |

| Fact (where they differ) | Nanbeige4.2-3B | Qwen3-VL-30B-A3B-Instruct |
| --- | --- | --- |
| 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 | 2025-11-01 |
| Agent reviews | none | 3/5 (4) |

Why the edge:
- Documentation and upkeep, Nanbeige4.2-3B +36: 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-VL-30B-A3B-Instruct 36 (The card misses limitations, languages and a cut-off (11).)
- Agent interface, Nanbeige4.2-3B +25: 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-VL-30B-A3B-Instruct 60 (A Jinja chat template in the repository (20).)
- Reach, Qwen3-VL-30B-A3B-Instruct +10: 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-VL-30B-A3B-Instruct 95 (Alibaba's own Q4_K_M GGUF is 18.6 GB, so with a fifth added it needs about 22 GB, or 23 GB with the vision file, and fits 24 GB (25).)