Head to head · Open-weight models you run yourself · October 2026 research run
InternVL3.5-GPT-OSS-20B-A4B-Preview vs North Mini Code 1.0
North Mini Code 1.0 scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D), and leads in every scored category. 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
InternVL3.5-GPT-OSS-20B-A4B-Preview D
Best for Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No quantised build from OpenGVLab, so about 51 GB at BF16
Best for Developers who want a coding agent on their own GPU with a permissive licence
Ahead on
- Reach, 85 against 65
- Risk, 60 against 55
- Agent interface, 85 against 45
- Documentation and upkeep, 36 against 28
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.
Agent interface North Mini Code 1.0 +40
InternVL3.5-GPT-OSS-20B-A4B-Preview 45
Chat template 20, a Jinja file in the repository, though it doesn't match the tokenizer. Tool-calling format 10 of 25, only the twin's inherited harmony template mentions tools. Trained tool calling 0, no evidence it was trained to call tools. Structured output 0. Reasoning control 10, a system prompt turns thinking on and the card says the reasoning comes back in think tags. Context 5, trained at 32K tokens.
North Mini Code 1.0 85
Chat template 20, chat_template.jinja in the repository (12,397 characters). Tool-calling format 25, the card documents how tools are declared (JSON schema through the chat template), how the call and its thinking go back into the history and how results are appended, and names the cohere_command4 tool-call parser for vLLM, which released vLLM has. Trained tool calling 20, the card says the model was specifically trained with tool-use capabilities for agentic coding, with reinforcement learning on verifiable tasks, and the template renders every call in a turn with thinking between them. Structured output 0, JSON schema is for describing tools. Reasoning control 10, the template has a reasoning_effort setting, and the card names the cohere_command4 reasoning parser, which returns thinking apart from the answer. Context 10, 256K tokens per the card, with 64K of output, and 500,000 positions in config.json. 20 + 25 + 20 + 0 + 10 + 10 = 85.
Reach North Mini Code 1.0 +20
InternVL3.5-GPT-OSS-20B-A4B-Preview 65
Memory 15 of 30, the only builds are BF16 at 42.5 GB by the repository's safetensors index, or 51 GB with a fifth added, which fits 64 GB. Runtimes 25, Transformers and vLLM load this repository, and SGLang, llama.cpp and Ollama (through llama.cpp b11963, which Ollama v0.40.14 pins) run the same weights in their GitHub format. Builds 0, OpenGVLab publishes no quantised build. Terms 15, Apache 2.0 with nothing added by the bases. Download 10, not gated. Hosted 0, no provider serves it.
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.
Documentation and upkeep North Mini Code 1.0 +8
InternVL3.5-GPT-OSS-20B-A4B-Preview 28
Model card 8 of 20, the family card misses limitations, context, languages and a cut-off. Training data 5, described without a cut-off. Last change 0, the last commit to either repository is 8 September 2025 and to OpenGVLab's reference code 22 September 2025, over a year before 4 November 2026. Responsiveness 10, OpenGVLab answered 3 of 8 questions across the two repositories, none since September 2025. Version policy 5, a first release. File health 0, the template uses markers the tokenizer doesn't have and contradicts the twin's template, and the card names the wrong language model in its licence line.
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
InternVL3.5-GPT-OSS-20B-A4B-Preview 55
File safety 25, safetensors only and no code in the repository. Provenance 15, the files are in the OpenGVLab organisation its GitHub links, with a checksum on every file. Safety evaluation 0 and agent guidance 0, nothing published. Licence risk 15, Apache 2.0 over Apache and MIT bases, with gpt-oss's usage policy asking only for lawful use. Security programme 0, no policy, security.txt or advisories.
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 | InternVL3.5-GPT-OSS-20B-A4B-Preview | North Mini Code 1.0 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 85 | North Mini Code 1.0 +20 |
| Risk | 20%20 | 55 | 60 | North Mini Code 1.0 +5 |
| Agent interface | 10%10 | 45 | 85 | North Mini Code 1.0 +40 |
| Documentation and upkeep | 10%10 | 28 | 36 | North Mini Code 1.0 +8 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 53.2/100 | C 61/100 |
Facts side by side
| Fact | InternVL3.5-GPT-OSS-20B-A4B-Preview | North Mini Code 1.0 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | Cohere |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-09-08 | 2026-07-29 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 1.8/5 (4) | none |
How the scores have moved
North Mini Code 1.0
No score change since it was listed.
Verdicts
InternVL3.5-GPT-OSS-20B-A4B-Preview
An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.
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
InternVL3.5-GPT-OSS-20B-A4B-Preview
- Serve with
vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768, which is our command; the card gives none for vLLM - Check the rendered prompt before relying on it, since the shipped template's <|im_start|> markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative
- Use Transformers 4.55.0 or later, as the card requires for this size
- For thinking, send the card's thinking system prompt and parse the reasoning out of the <think> tags, with temperature 0.6 and sampling on as the card advises
- Keep inputs within 32K tokens, the length it was trained at, whatever the config says
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, InternVL3.5-GPT-OSS-20B-A4B-Preview or North Mini Code 1.0?
North Mini Code 1.0 scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D), and leads in every scored category.
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- North Mini Code 1.0 vs Qwen3-Coder-Next
- North Mini Code 1.0 vs Qwen3-Omni-30B-A3B-Instruct
- North Mini Code 1.0 vs Qwen3-VL-2B-Instruct
- North Mini Code 1.0 vs Qwen3-VL-30B-A3B-Instruct
- North Mini Code 1.0 vs Qwen3-VL-32B-Instruct
- North Mini Code 1.0 vs Qwen3-VL-4B-Instruct
- North Mini Code 1.0 vs Qwen3-VL-8B-Instruct
- North Mini Code 1.0 vs Qwopus3.8-27B-Flash-V2
- North Mini Code 1.0 vs Recursive Flint
- North Mini Code 1.0 vs Ripple-65B Preview
- North Mini Code 1.0 vs SenseNova-Loop-9B-Preview
- North Mini Code 1.0 vs SmolLM3-3B
- North Mini Code 1.0 vs Spark-X2.6-4B
- North Mini Code 1.0 vs Step 3.7 Flash
- North Mini Code 1.0 vs Swift 1.5 Qwen3.8-27B
- North Mini Code 1.0 vs Swift 1.5 Qwen3.8-Flash-Next
- North Mini Code 1.0 vs ThinkingCap (Qwen3.8 27B)
- North Mini Code 1.0 vs Baidu Unlimited-OCR-2
- North Mini Code 1.0 vs WeVisOne-VL-2B
- North Mini Code 1.0 vs WeVisOne-VL-4B
- North Mini Code 1.0 vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-north-mini-code-1-0.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json·/api/v1/tools/north-mini-code-1-0.json - From a terminal
anchor compare internvl3-5-gpt-oss-20b-a4b-preview north-mini-code-1-0(the CLI) - Over MCP
compare_tools {"a": "internvl3-5-gpt-oss-20b-a4b-preview", "b": "north-mini-code-1-0"}at/mcp, no key