# Laguna M.1 vs Nanbeige4.2-3B

> Nanbeige4.2-3B scores 61 (C) to Laguna M.1's 56.7 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b
- Markdown: https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.md (~8,800 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

Nanbeige4.2-3B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories. Both do open-weight models you run yourself.

- Laguna M.1: grade C, 56.7/100, rank #112 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-m-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json
- Nanbeige4.2-3B: grade C, 61/100, rank #78 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/nanbeige-4-2-3b.md · JSON https://www.anchorterminal.com/api/v1/tools/nanbeige-4-2-3b.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### Laguna M.1 (C)

Good for: Teams with a multi-GPU Blackwell or Hopper server that want a large coding agent model under Apache 2.0.

Watch for: The smallest build needs about 167 GB, more than a 128 GB machine

### Nanbeige4.2-3B (C)

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
- Documentation and upkeep, 72 against 36

Watch for: Its own architecture: Transformers loads it only with the repository's code


## Why the edge

### Documentation and upkeep: Nanbeige4.2-3B +36

- Laguna M.1 (36): Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 5, the report describes sources and filtering but gives no cut-off. Last change 10, 14 July 2026, 113 days ago. Responsiveness 0, the one discussion's only reply is from someone outside the poolside organisation. Version policy 5, a first open release with nothing replaced. File health 5, generation config and template disagree on the thinking default and the FP8 build's Docker files name different image tags.
- 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 the card. Training data 5, A general description of how the fine-tuning and reinforcement learning data was built and filtered, with no sources, sizes or cut-off. Last change 15, the last commit, on 11 September 2026, updated modeling_nanbeige.py, 60 days before this check and within 90. Responsiveness 20, Of the 34 most recent discussions that aren't pull requests (21 July to 10 September 2026), 20 have a reply from a Nanbeige member, which is most. Version policy 5, Nanbeige's earlier models (Nanbeige4-3B, 4.1-3B) stay in their own repositories, as the Base, FP8, 8-bit and DSpark builds of this one do. File health 10, Config, tokenizer config, template and card agree on the architecture and the 262,144 tokens. 17 + 5 + 15 + 20 + 5 + 10 = 72.

### Reach: Nanbeige4.2-3B +15

- Laguna M.1 (70): Memory 5 of 30, the smallest 4-bit build is Poolside's 139.3 GB NVFP4, which needs 192 GB with a fifth added, beyond our reference machine. Runtimes 25, released llama.cpp, Ollama (through the llama.cpp release it pins), vLLM, SGLang and Transformers run the laguna architecture. Builds 15, FP8 and NVFP4 from Poolside. Terms 15, Apache 2.0 with nothing binding added. Download 10, nothing is gated. Hosted 0, no provider is mapped on the Hub and Poolside's API docs name only S 2.1.
- 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. bartowski's GGUF isn't read for this line. Runtimes 15, Released SGLang 0.5.23 has the model (srt/models/nanbeige.py) with its parsers, llama.cpp b12242 has the nanbeige architecture, and vLLM 0.33.0 names NanbeigeForCausalLM in its registry, served through its Transformers backend. Builds 15, Quantised builds from Nanbeige at two precisions, FP8 and 8-bit GPTQ, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence, with no use policy or other terms on the card. Download 10, the Hub API reports gated false for the model and its FP8 and 8-bit repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and no Nanbeige or BOSS Zhipin API for it was found. 30 + 15 + 15 + 15 + 10 + 0 = 85.

## Score by category

| Category | Weight | Laguna M.1 | Nanbeige4.2-3B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 70 | 85 | Nanbeige4.2-3B +15 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 85 | 85 | even |
| Documentation and upkeep | 10% (10 this run) | 36 | 72 | Nanbeige4.2-3B +36 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **56.7 · C** | **61 · C** | |

## Facts side by side

| Fact | Laguna M.1 | Nanbeige4.2-3B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Poolside | Nanbeige LLM Lab (BOSS Zhipin) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 (Hub metadata only; the repository has no LICENSE file) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-14 | 2026-09-11 |
| Terms last updated | 2026-07-21 | no document linked |
| Privacy policy last updated | 2026-07-21 | no document linked |
| Customer content may train models | yes, with an opt-out | not read yet |
| Terms restrict automated access | not found in the text | not read yet |
| Terms restrict benchmarking | not found in the text | not read yet |
| Terms or service can change without notice | yes | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Agent reviews | 2.5/5 (4) | none |

## How the scores have moved

### Laguna M.1

- +1.2 on 4 November 2026: correction

### Nanbeige4.2-3B

No score change since it was listed.

## Verdicts

**Laguna M.1.** A large open-weight coding and agent model under plain Apache 2.0, for teams with a multi-GPU server. Its smallest build needs about 167 GB, more than a 128 GB machine. Released llama.cpp, Ollama, vLLM, SGLang and Transformers code runs the architecture. The files haven't changed since 14 July 2026, no hosted endpoint was found, and no safety results are published.

**Nanbeige4.2-3B.** A small model built for agent work, with tool calling it was trained for, a thinking switch and a 256K context in about 5 GB, under Apache 2.0, from a lab that answers most questions. Its architecture is its own, so check your runtime: SGLang and llama.cpp have it, Transformers needs the repository's code, and Nanbeige ships no GGUF.

## Before you call either

### Laguna M.1

1. Run the NVFP4 build on Blackwell GPUs with `vllm serve poolside/Laguna-M.1-NVFP4 --tensor-parallel-size 2 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on vLLM 0.21.0 or later
2. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{"enable_thinking": true}'`, which Poolside recommends for agentic coding
3. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped
4. Sampling per the card is temperature 1.0 and top_k 20
5. The FP8 build's Docker image and serve.sh predate upstream support and set a 4,096-token context, so prefer a released vLLM
6. It doesn't fit our 128 GB reference machine at any published precision
7. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented

### Nanbeige4.2-3B

1. Serve it with SGLang 0.5.23 or later and pass `--tool-call-parser nanbeige --reasoning-parser nanbeige`
2. Pass `tools` in the request. The card recommends `tool_call_format="xml"`
3. Set `preserve_thinking` true for multi-turn tool use and coding, false for plain chat
4. Use temperature 1.0 for agent and tool work and 0.6 for reasoning and chat, per the card
5. For llama.cpp use b12242 or later. The GGUF files on the Hub are bartowski's, not Nanbeige's
6. If you load it with Transformers, read modeling_nanbeige.py first: trust_remote_code runs it

## Questions

### Which is better for AI agents, Laguna M.1 or Nanbeige4.2-3B?

Nanbeige4.2-3B scores 61 (C) on agent readiness against Laguna M.1's 56.7 (C), and leads in 2 of 4 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-m-1-vs-nanbeige-4-2-3b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "laguna-m-1", "b": "nanbeige-4-2-3b"}`. From a terminal: `anchor compare laguna-m-1 nanbeige-4-2-3b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-m-1.json and https://www.anchorterminal.com/api/v1/tools/nanbeige-4-2-3b.json

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- [Laguna M.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-m-1-vs-nemotron-3-super-120b-a12b.md)
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- [Laguna M.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-397b.md)
- [Laguna M.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-9b.md)
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- [Laguna M.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.md)
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- [Laguna M.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-122b-a10b.md)
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- [Laguna M.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-397b-a17b.md)
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- [Laguna M.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-5-9b.md)
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- [Laguna M.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-6-35b-a3b.md)
- [Laguna M.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-27b.md)
- [Laguna M.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-8-flash-next.md)
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- [Laguna M.1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-2b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-30b-a3b-instruct.md)
- [Laguna M.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-vl-32b-instruct.md)
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- [Laguna M.1 vs Recursive Flint](https://www.anchorterminal.com/compare/laguna-m-1-vs-recursive-flint.md)
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- [Laguna M.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-m-1-vs-smollm3-3b.md)
- [Laguna M.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-spark-x2-6-4b.md)
- [Laguna M.1 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/laguna-m-1-vs-step-3-7-flash.md)
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- [Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.md)
- [Laguna M.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-m-1-vs-thinkingcap-qwen3-8-27b.md)
- [Laguna M.1 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/laguna-m-1-vs-unlimited-ocr-2.md)
- [Laguna M.1 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-2b.md)
- [Laguna M.1 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/laguna-m-1-vs-wevisone-vl-4b.md)
- [Laguna M.1 vs ZAYA1-8B](https://www.anchorterminal.com/compare/laguna-m-1-vs-zaya1-8b.md)
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- [MiMo-V2.6-Flash-RL vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-nanbeige-4-2-3b.md)
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- [MiniCPM-V 4.7 35B-A3B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-nanbeige-4-2-3b.md)
- [MiniCPM5-2B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-nanbeige-4-2-3b.md)
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- [Mistral Large 4 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/mistral-large-4-vs-nanbeige-4-2-3b.md)
- [Muse Glimmer 30B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-nanbeige-4-2-3b.md)
- [Nanbeige4.2-3B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nanbeige-4-3-33b.md)
- [Nanbeige4.2-3B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-5-bolt-e4b-4gb.md)
- [Nanbeige4.2-3B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-5-lightning-30b-a3b.md)
- [Nanbeige4.2-3B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-nano-30b-a3b.md)
- [Nanbeige4.2-3B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-nano-4b.md)
- [Nanbeige4.2-3B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Nanbeige4.2-3B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-super-120b-a12b.md)
- [Nanbeige4.2-3B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-nemotron-3-ultra-550b-a55b.md)
- [Nanbeige4.2-3B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-north-mini-code-1-0.md)
- [Nanbeige4.2-3B vs occamy-1.0](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-occamy-1-0.md)
- [Nanbeige4.2-3B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-olmo-3-7b-think.md)
- [Nanbeige4.2-3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-122b.md)
- [Nanbeige4.2-3B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-35b-a3b.md)
- [Nanbeige4.2-3B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-397b.md)
- [Nanbeige4.2-3B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-9b.md)
- [Nanbeige4.2-3B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-otel-2-0-llm-31b-it.md)
- [Nanbeige4.2-3B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen-agentworld-35b-a3b.md)
- [Nanbeige4.2-3B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-30b-a3b-instruct-2507.md)
- [Nanbeige4.2-3B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-4b-instruct-2507.md)
- [Nanbeige4.2-3B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-0-8b.md)
- [Nanbeige4.2-3B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-122b-a10b.md)
- [Nanbeige4.2-3B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-2b.md)
- [Nanbeige4.2-3B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-397b-a17b.md)
- [Nanbeige4.2-3B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-4b.md)
- [Nanbeige4.2-3B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-5-9b.md)
- [Nanbeige4.2-3B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-6-27b.md)
- [Nanbeige4.2-3B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-6-35b-a3b.md)
- [Nanbeige4.2-3B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-8-27b.md)
- [Nanbeige4.2-3B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-8-flash-next.md)
- [Nanbeige4.2-3B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-coder-30b-a3b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-coder-next.md)
- [Nanbeige4.2-3B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-omni-30b-a3b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-2b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-30b-a3b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-32b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-4b-instruct.md)
- [Nanbeige4.2-3B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwen3-vl-8b-instruct.md)
- [Nanbeige4.2-3B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-qwopus3-8-27b-flash-v2.md)
- [Nanbeige4.2-3B vs Recursive Flint](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-recursive-flint.md)
- [Nanbeige4.2-3B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ripple-65b-preview.md)
- [Nanbeige4.2-3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-sensenova-loop-9b-preview.md)
- [Nanbeige4.2-3B vs SmolLM3-3B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-smollm3-3b.md)
- [Nanbeige4.2-3B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-spark-x2-6-4b.md)
- [Nanbeige4.2-3B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-step-3-7-flash.md)
- [Nanbeige4.2-3B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-swift-1-5-qwen3-8-27b.md)
- [Nanbeige4.2-3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-swift-1-5-qwen3-8-flash-next.md)
- [Nanbeige4.2-3B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-thinkingcap-qwen3-8-27b.md)
- [Nanbeige4.2-3B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-unlimited-ocr-2.md)
- [Nanbeige4.2-3B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-wevisone-vl-2b.md)
- [Nanbeige4.2-3B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-wevisone-vl-4b.md)
- [Nanbeige4.2-3B vs ZAYA1-8B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-zaya1-8b.md)

---

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