Head to head · Open-weight models you run yourself · October 2026 research run
Laguna XS 2.1 vs North Mini Code 1.0
Laguna XS 2.1 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 reach and 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
Best for Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.
Ahead on
- Documentation and upkeep, 46 against 36
Watch for
No reply from Poolside to any discussion, including reports about the tokenizer and remote code
Best for Developers who want a coding agent on their own GPU with a permissive licence
Ahead on
- Reach, 85 against 80
- 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 Laguna XS 2.1 +10
Laguna XS 2.1 46
Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 10, the linked report describes sources and filtering and Poolside's S 2.1 post gives the shared November 2025 cut-off. Last change 15, 19 August 2026, 76 days back. Responsiveness 0, Poolside answered none of the 6 discussions. Version policy 5, XS.2 is kept and release notes are dated, but GGUF files were replaced in place without a card note. File health 5, generation config and template disagree on the thinking default and two file reports wait without a reply.
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 Last change 10, the main repository last changed on 15 June 2026 (outdated chat templates removed), 148 days before this check, and the draft model's repository on 29 July, 104 days.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.
Reach North Mini Code 1.0 +5
Laguna XS 2.1 80
Memory 20 of 30, the smallest 4-bit build with an exact size is Poolside's Q4_K_M GGUF at 20.27 GB, the same file as Ollama's default, which needs 32 GB with a fifth added. Runtimes 25, released llama.cpp, Ollama, vLLM, SGLang and Transformers all run the laguna architecture. Builds 15, Poolside publishes FP8, INT4, NVFP4, MLX and GGUF builds. Terms 10, OpenMDW-1.1 is permissive but not OSI-approved. Download 10, nothing is gated. Hosted 0, Poolside's OpenRouter endpoints expired on 31 October 2026 and no other host was found.
North Mini Code 1.0 85
Memory 25, the smallest build from Cohere is the w4a16 repository, 19.38 GB, and 19.38 GB × 1.2 = 23.3 GB, within 24 GB. Unsloth's GGUF isn't read for this line. Runtimes 20, Released vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 have the cohere2_moe model, and llama.cpp b12242 has the cohere2moe architecture. Builds 15, Quantised builds from Cohere at two precisions, FP8 and 4-bit weights (w4a16), each in its own repository. Terms 15, Apache 2.0 in the metadata and on the card, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds 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. 25 + 20 + 15 + 15 + 10 + 0 = 85.
Risk North Mini Code 1.0 +5
Laguna XS 2.1 55
File safety 15 of 25, safetensors and GGUF only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM commands use trust_remote_code. Provenance 15, the verified poolside organisation that Poolside's blog links, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, OpenMDW-1.1 has no use policy, threshold or revocation clause. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.
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
| Category | Weight this run | Laguna XS 2.1 | North Mini Code 1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 80 | 85 | North Mini Code 1.0 +5 |
| Risk | 20%20 | 55 | 60 | North Mini Code 1.0 +5 |
| Agent interface | 10%10 | 85 | 85 | even |
| Documentation and upkeep | 10%10 | 46 | 36 | Laguna XS 2.1 +10 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 61/100 | C 61/100 |
Facts side by side
| Fact | Laguna XS 2.1 | North Mini Code 1.0 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Poolside | Cohere |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | OpenMDW-1.1 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-19 | 2026-07-29 |
| 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 | 2.8/5 (4) | none |
How the scores have moved
North Mini Code 1.0
No score change since it was listed.
Verdicts
Laguna XS 2.1
A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.
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
Laguna XS 2.1
- Quickest start is
ollama run laguna-xs-2.1, 20 GB of files, the same Q4_K_M as Poolside's GGUF - On our reference machine use
llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB) - With vLLM use
--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice, on a build with vllm-project/vllm#47311, or--tool-call-parser glm47on older builds - Thinking is off in the template unless you pass
enable_thinkingtrue or start the server with--default-chat-template-kwargs '{"enable_thinking": true}', which Poolside recommends for agentic coding - Pass earlier reasoning back as
reasoning_contentin the history, since the card says reasoning may stop in later steps if it's dropped - Sampling per the card is temperature 1.0 and top_k 20
- The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
North Mini Code 1.0
- Serve it with vLLM 0.33.0 or later and
--tool-call-parser cohere_command4 --reasoning-parser cohere_command4 --enable-auto-tool-choice, withcohere_melodyinstalled - Pass the model's thinking back with its tool calls on every turn. The card says results drop without it
- Describe tools in JSON schema and append tool results as a dictionary with the tool role
- Use temperature 1.0 and top_p 0.95
- For llama.cpp the GGUF files are Unsloth's or bartowski's conversions, not Cohere's
- It's text only. Don't send images
Questions
Which is better for AI agents, Laguna XS 2.1 or North Mini Code 1.0?
Laguna XS 2.1 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 reach and risk.
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Machine-readable
- This page as Markdown
/compare/laguna-xs-2-1-vs-north-mini-code-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/laguna-xs-2-1.json·/api/v1/tools/north-mini-code-1-0.json - From a terminal
anchor compare laguna-xs-2-1 north-mini-code-1-0(the CLI) - Over MCP
compare_tools {"a": "laguna-xs-2-1", "b": "north-mini-code-1-0"}at/mcp, no key