# MiniCPM-o 4.5 vs SenseNova-Loop-9B-Preview

> MiniCPM-o 4.5 scores 61 (C) to SenseNova-Loop-9B-Preview's 46.8 (D) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-sensenova-loop-9b-preview
- Markdown: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-sensenova-loop-9b-preview.md (~10,000 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 scores 61 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 2 of 4 scored categories. SenseNova-Loop-9B-Preview 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
- SenseNova-Loop-9B-Preview: grade D, 46.8/100, rank #155 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.md · JSON https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.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 40
- Documentation and upkeep, 66 against 44

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

### SenseNova-Loop-9B-Preview (D)

Good for: Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today

Ahead on:
- Risk, 50 against 40
- Agent interface, 60 against 35

Watch for: No released runtime runs it. vLLM and SGLang need unmerged pull requests


## Why the edge

### Reach: MiniCPM-o 4.5 +50

- 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.
- SenseNova-Loop-9B-Preview (40): Memory 15, the only build is the safetensors set, 38.14 GB with its MTP head, since the Hub counts 9.41B of its parameters in F32. Runtimes 0, none of the six runs it in a released version. Builds 0, SenseNova publishes one set of weights and no quantised build. Terms 15, Apache 2.0 in the card's metadata and on the card, which links the LICENSE in the GitHub repository, and nothing added. Download 10, the Hub API reports gated false 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 the card names no API that serves it. 15 + 0 + 0 + 15 + 10 + 0 = 40.

### Agent interface: SenseNova-Loop-9B-Preview +25

- 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.
- SenseNova-Loop-9B-Preview (60): Chat template 20, chat_template.jinja in the repository (7,756 characters). Tool-calling format 10, only the template says it: a tools block, and calls written as tool_call blocks with function and parameter tags. Trained tool calling 10, the card says the training recipes include tool trajectories and that the model is for agentic workflows. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the card documents enable_thinking in the chat template call, on or off per request, and the template puts the reasoning in think tags ahead of the answer. Context 10, 262,144 tokens in training, per the card's specification table, and config.json gives the language model 262,144 positions. 20 + 10 + 10 + 0 + 10 + 10 = 60.

### Documentation and upkeep: MiniCPM-o 4.5 +22

- 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.
- SenseNova-Loop-9B-Preview (44): Model card 14, Intended use, the architecture, the parameter counts, the training context and the languages (in the metadata) are on the card. Training data 5, one general sentence on the recipes, with no sources, sizes or cut-off. Last change 20, the last commit, on 2 November 2026, reworked the speculative decoding section of the card, 8 days before this check. Responsiveness 0, none of the 5 discussions that aren't pull requests (30 October to 9 November 2026) has a reply from a sensenova member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, labelled a preview, with dated news on the card. File health 0, the files contradict the card on precision. 14 + 5 + 20 + 0 + 5 + 0 = 44.

### Risk: SenseNova-Loop-9B-Preview +10

- 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.
- SenseNova-Loop-9B-Preview (50): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the sensenova organisation, which the GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on instructions inside tool results or images. Licence risk 15, Apache 2.0 with no use policy, no threshold and no right to change the terms. Security programme 5, SenseTime's about page gives a security contact (5). 15 + 15 + 0 + 0 + 15 + 5 = 50.

## Score by category

| Category | Weight | MiniCPM-o 4.5 | SenseNova-Loop-9B-Preview | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 90 | 40 | MiniCPM-o 4.5 +50 |
| Risk | 20% (20 this run) | 40 | 50 | SenseNova-Loop-9B-Preview +10 |
| Agent interface | 10% (10 this run) | 35 | 60 | SenseNova-Loop-9B-Preview +25 |
| Documentation and upkeep | 10% (10 this run) | 66 | 44 | MiniCPM-o 4.5 +22 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **46.8 · D** | |

## Facts side by side

| Fact | MiniCPM-o 4.5 | SenseNova-Loop-9B-Preview |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenBMB | SenseTime (SenseNova) |
| 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 | 2026-11-02 |
| Terms last updated | no document linked | not read yet |
| 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.

**SenseNova-Loop-9B-Preview.** An unusual architecture under Apache 2.0, with a 256K training context, a thinking switch and tool calling in the template. It's a preview in practice too: no released runtime runs it, loading it runs the repository's code, the files are twice the size the card implies, and nobody from SenseNova has answered a question yet.

## 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

### SenseNova-Loop-9B-Preview

1. Read modeling_sensenova_loop.py before you load it. trust_remote_code runs it
2. Pin transformers 5.18.0, the version the card checked
3. Load with dtype=torch.bfloat16 as the card does, or the 38 GB of F32 weights stay at full size
4. Pass enable_thinking=False to apply_chat_template for a direct answer
5. Tool calls come back as tool_call blocks with function and parameter tags. Parse them yourself, since no runtime ships a parser
6. Wait for the vLLM or SGLang pull request to land in a release before putting it behind an API

## Questions

### Which is better for AI agents, MiniCPM-o 4.5 or SenseNova-Loop-9B-Preview?

MiniCPM-o 4.5 scores 61 (C) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in 2 of 4 scored categories. SenseNova-Loop-9B-Preview leads on risk and agent interface.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-sensenova-loop-9b-preview.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-sensenova-loop-9b-preview.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm-o-4-5", "b": "sensenova-loop-9b-preview"}`. From a terminal: `anchor compare minicpm-o-4-5 sensenova-loop-9b-preview`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-o-4-5.json and https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.json

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