Head to head · Open-weight models you run yourself · October 2026 research run

Nanbeige4.2-3B vs North Mini Code 1.0

Nanbeige4.2-3B and North Mini Code 1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). North Mini Code 1.0 leads on risk. Both do open-weight models you run yourself.

Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons

Which one, for what

Nanbeige4.2-3B C

Best for Local agents that need tool calling and a long context on a laptop or a small GPU

Ahead on

  • Documentation and upkeep, 72 against 36

Watch for

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

North Mini Code 1.0 C

Best for Developers who want a coding agent on their own GPU with a permissive licence

Ahead on

  • Risk, 60 against 55

Watch for

No limitations, safety results, languages or data description on the card

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

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 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.

North Mini Code 1.0 36

Model card 11, Intended use, the architecture, the parameters and the context are on the card. Training data 0, the card gives the training method and nothing about the data. Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days. Responsiveness 0, none of the 11 most recent discussions that aren't pull requests (7 June to 6 November 2026) has a reply from a CohereLabs member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, with each build in its own repository. File health 10, Config, template and card agree on the architecture, and the June commit that removed broken templates says so. 11 + 0 + 10 + 0 + 5 + 10 = 36.

Risk North Mini Code 1.0 +5

Nanbeige4.2-3B 55

File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the Nanbeige organisation (Nanbeige LLM Lab), which the lab's arXiv report for this model links, so the publisher's own account, although the Hub hasn't verified it (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions: the limitations section says outputs may be inaccurate, biased or harmful. Licence risk 15, Apache 2.0 has no use policy, no threshold and no clause letting the licensor change or revoke it. Security programme 5, BOSS Zhipin runs a security response centre for reporting flaws in its products, as read for the Nanbeige4.3-33B listing (5), though nothing links it to the model. 15 + 15 + 0 + 5 + 15 + 5 = 55.

North Mini Code 1.0 60

File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Cohere's verified CohereLabs organisation, which cohere.com links to per our other Cohere listings (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 5, Cohere's trust centre holds a responsible disclosure policy with a bug bounty, as recorded on our Cohere listings (5). 25 + 15 + 0 + 0 + 15 + 5 = 60.

Score by category

CategoryWeight this runNanbeige4.2-3BNorth Mini Code 1.0Edge
Capability35%pendingpendingpendingnot scored in this run
Reach25%258585even
Risk20%205560North Mini Code 1.0 +5
Agent interface10%108585even
Documentation and upkeep10%107236Nanbeige4.2-3B +36
Negative events≤1500
TotalC 61/100C 61/100

Facts side by side

FactNanbeige4.2-3BNorth Mini Code 1.0
KindOpen-weight modelOpen-weight model
VendorNanbeige LLM Lab (BOSS Zhipin)Cohere
Hosted endpointno (local only)no (local only)
Transports
AuthNoneNone
PricingFreeFree
x402nono
LicenceApache-2.0 (Hub metadata only; the repository has no LICENSE file)Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-09-112026-07-29
Terms last updatedno document linkedno document linked
Privacy policy last updatedno document linkedno document linked

Verdicts

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.

North Mini Code 1.0

A coding agent model that fits one 24 GB GPU at 4 bits, trained for tool use, with a 256K context, Apache 2.0 and four released runtimes. It's a research release and reads like one: nothing on limitations, safety or data, the card's run instructions are out of date, and Cohere hasn't answered a question on the repository.

Before you call either

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

North Mini Code 1.0

  1. Serve it with vLLM 0.33.0 or later and --tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice, with cohere_melody installed
  2. Pass the model's thinking back with its tool calls on every turn. The card says results drop without it
  3. Describe tools in JSON schema and append tool results as a dictionary with the tool role
  4. Use temperature 1.0 and top_p 0.95
  5. For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's
  6. It's text only. Don't send images

Questions

Which is better for AI agents, Nanbeige4.2-3B or North Mini Code 1.0?

Nanbeige4.2-3B and North Mini Code 1.0 score within a point of each other on agent readiness, 61 (C) and 61 (C). North Mini Code 1.0 leads on risk.

Other comparisons with Nanbeige4.2-3B or North Mini Code 1.0

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