# MiniCPM-o 4.5 vs North Mini Code 1.0

> MiniCPM-o 4.5 and North Mini Code 1.0 score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0
- Markdown: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0.md (~9,700 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

MiniCPM-o 4.5 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 and agent interface. Both do open-weight models you run yourself.

- MiniCPM-o 4.5: grade C, 61/100, rank #48 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-o-4-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json
- North Mini Code 1.0: grade C, 61/100, rank #80 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/north-mini-code-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.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
- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md
- All 581 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md

## Which one, for what

### MiniCPM-o 4.5 (C)

Good for: Agents that need a local model to see, hear and speak on a laptop or a single small GPU, with a plain licence.

Ahead on:
- Reach, 90 against 85
- Documentation and upkeep, 66 against 36

Watch for: Speech output and full duplex need trust_remote_code with Transformers 4.51.0 or OpenBMB's llama.cpp-omni

### North Mini Code 1.0 (C)

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

Ahead on:
- Risk, 60 against 40
- Agent interface, 85 against 35

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


## Why the edge

### Agent interface: North Mini Code 1.0 +50

- MiniCPM-o 4.5 (35): Chat template 20, a Jinja template in the tokenizer config. Tool-calling format 10 of 25, only the inherited Qwen3 template says how tools work. Trained tool calling 0, OpenBMB never mentions tool use. Structured output 0, not documented. Reasoning control 0, thinking turns on and off per request but nobody says where the reasoning comes back. Context 5, 40,960 tokens. Read as an omni model, it takes images, video and audio and returns text and streaming speech, which the card documents with code.
- 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.

### Documentation and upkeep: MiniCPM-o 4.5 +30

- MiniCPM-o 4.5 (66): Model card 11 of 20, limitations, context length and a knowledge cut-off are missing. Training data 5, described by kind without sources, sizes or a cut-off. Last change 20, the card changed on 24 October 2026. Responsiveness 10, OpenBMB answered half of the 12 questions. Version policy 10, earlier models stay in their own repositories and releases are dated. File health 10, the files agree and the two bug reports have replies.
- 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 +20

- MiniCPM-o 4.5 (40): File safety 5 of 25, two pickle files sit in the speech stage and the documented load runs repository code. Provenance 15, the files are in the openbmb organisation OpenBMB's GitHub links, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only, nothing about voice cloning misuse, prompt injection or refusals. Licence risk 15, plain Apache 2.0. Security programme 0, no security.txt, policy 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.

### Reach: MiniCPM-o 4.5 +5

- MiniCPM-o 4.5 (90): Memory 30, OpenBMB's 4-bit GGUF with its vision file is 5.9 GB, about 7 GB with a fifth added. Runtimes 15 of 25, released vLLM, llama.cpp and Ollama run it, while Transformers 5.22.1 still needs OpenBMB's remote code and SGLang 0.5.23 supports only the older 2.6. Builds 15, GGUF at several precisions plus AWQ and GPTQ. Terms 15, plain Apache 2.0. Download 10, nothing gated. Hosted 5, OpenBMB's own API 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.

## Score by category

| Category | Weight | MiniCPM-o 4.5 | North Mini Code 1.0 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 85 | MiniCPM-o 4.5 +5 |
| Risk | 20% (20 this run) | 40 | 60 | North Mini Code 1.0 +20 |
| Agent interface | 10% (10 this run) | 35 | 85 | North Mini Code 1.0 +50 |
| Documentation and upkeep | 10% (10 this run) | 66 | 36 | MiniCPM-o 4.5 +30 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **61 · C** | |

## Facts side by side

| Fact | MiniCPM-o 4.5 | North Mini Code 1.0 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenBMB | Cohere |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0; built from Qwen3-8B, SigLIP2, Whisper-medium and CosyVoice2, all Apache 2.0 on their Hub cards | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-24 | 2026-07-29 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.8/5 (4) | none |

## Verdicts

**MiniCPM-o 4.5.** A small omni cousin that sees, listens and talks back, with full-duplex speech and voice cloning, in about 7 GB at 4-bit through llama.cpp or Ollama for text and images. Speech output needs OpenBMB's remote code or llama.cpp-omni, and 28 GB of GPU for the full demo. The main risks are repository code and pickle files and 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

### MiniCPM-o 4.5

1. Quickest start for text and images is `ollama run openbmb/minicpm-o4.5`, about 6 GB
2. With vLLM 0.16.0 or later pass `--trust-remote-code`, and send `stop_token_ids` [151643, 151645] as OpenBMB's guide does
3. vLLM, llama.cpp and Ollama return text only; for speech out use the card's Transformers 4.51.0 code or OpenBMB's llama.cpp-omni
4. In llama.cpp pass both the language GGUF and MiniCPM-o-4_5-vision-F16.gguf with `--mmproj`, and use `--jinja --reasoning-budget 0` to turn thinking off
5. Keep prompts within 40,960 tokens
6. Don't rely on tool calls or JSON output, neither is documented; validate any you get

### 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, MiniCPM-o 4.5 or North Mini Code 1.0?

MiniCPM-o 4.5 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 and agent interface.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-north-mini-code-1-0.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm-o-4-5", "b": "north-mini-code-1-0"}`. From a terminal: `anchor compare minicpm-o-4-5 north-mini-code-1-0`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json and https://www.anchorterminal.com/api/v1/tools/north-mini-code-1-0.json

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