Head to head · Open-weight models you run yourself · October 2026 research run
InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM-V 4.7 35B-A3B
MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D), and leads in 3 of 4 scored categories. 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 Agents that need to read screenshots, documents and video on a local machine with 24 to 32 GB for the model, under a permissive licence
Ahead on
- Reach, 90 against 65
- Agent interface, 70 against 45
- Documentation and upkeep, 68 against 28
Watch for
No limitations section, safety results, agent-use guidance or security contact
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 MiniCPM-V 4.7 35B-A3B +40
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.
MiniCPM-V 4.7 35B-A3B 68
Model card 8, it covers intended use, architecture and parameters but not limitations, context length, languages or a knowledge cut-off. Training data 0, none described. Last change 20, a commit on 3 November 2026. Responsiveness 20, OpenBMB answered 8 of 12 discussions. Version policy 10, earlier versions keep their repositories and the changes are dated and described. File health 10, the files agree. 8 + 0 + 20 + 20 + 10 + 10 = 68.
Reach MiniCPM-V 4.7 35B-A3B +25
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.
MiniCPM-V 4.7 35B-A3B 90
Memory 25, since OpenBMB's IQ4_XS GGUF with its vision projector is 19.6 GB and needs about 23.6 GB with the fifth added, which fits 24 GB, while its Q4_K_M GGUF, 4-bit safetensors builds and Ollama entry need 32 GB. Runtimes 25, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.18.0 and later, llama.cpp's own MiniCPM-V 4.7 support and OpenBMB's entry on Ollama. Builds 15, OpenBMB publishes FP8, three 4-bit safetensors builds and GGUF. Terms 15, Apache 2.0 with nothing added. Download 10, nothing is gated. Hosted 0, no inference provider is mapped. 25 + 25 + 15 + 15 + 10 + 0 = 90.
Agent interface MiniCPM-V 4.7 35B-A3B +25
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.
MiniCPM-V 4.7 35B-A3B 70
Chat template 20, a Jinja file in the repository. Tool-calling format 10, the card shows the tools array going in but not the call coming back, and names no parser. Trained tool calling 20, the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, enable_thinking per request, off by default, with the trace between markers. Context 10, 262,144 tokens native.
Score by category
| Category | Weight this run | InternVL3.5-GPT-OSS-20B-A4B-Preview | MiniCPM-V 4.7 35B-A3B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 90 | MiniCPM-V 4.7 35B-A3B +25 |
| Risk | 20%20 | 55 | 55 | even |
| Agent interface | 10%10 | 45 | 70 | MiniCPM-V 4.7 35B-A3B +25 |
| Documentation and upkeep | 10%10 | 28 | 68 | MiniCPM-V 4.7 35B-A3B +40 |
| 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 | MiniCPM-V 4.7 35B-A3B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | OpenBMB |
| 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 | 2026-11-03 |
| 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
MiniCPM-V 4.7 35B-A3B
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.
MiniCPM-V 4.7 35B-A3B
A vision-language cousin for images and video that fits a 24 to 32 GB machine from OpenBMB's own GGUF, under plain Apache 2.0, with a publisher that answers. The card says little about limits, training data or how tool calls come back, so test the tool format in your runtime before relying on it.
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
MiniCPM-V 4.7 35B-A3B
- Start it with
llama-server -hf openbmb/MiniCPM-V-4.7-35B-A3B-gguf:Q4_K_M --jinja, orollama run openbmb/minicpm-v4.7:35b-a3b - For image input in llama.cpp add
mmproj-model-f16.gguf, or the 4x projector for more visual detail at a higher cost - The GGUF files at the repository root have thinking off. Use the files in
thinking/when you want the trace - With Transformers pass
enable_thinkingtoapply_chat_template, and passdownsample_modeto bothapply_chat_templateandgenerate - Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends
- Check tool calls in your runtime first, since the card names no parser. The template uses the Qwen3.5 function-block format
- Validate JSON output yourself, since structured output isn't documented
Questions
Which is better for AI agents, InternVL3.5-GPT-OSS-20B-A4B-Preview or MiniCPM-V 4.7 35B-A3B?
MiniCPM-V 4.7 35B-A3B scores 61 (C) on agent readiness against InternVL3.5-GPT-OSS-20B-A4B-Preview's 53.2 (D), and leads in 3 of 4 scored categories.
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- MiniCPM-V 4.7 35B-A3B vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 35B-A3B vs Qwen3-30B-A3B-Instruct-2507
- MiniCPM-V 4.7 35B-A3B vs Qwen3-4B-Instruct-2507
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-0.8B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-122B-A10B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-2B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-397B-A17B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-4B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.5-9B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.6-27B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.6-35B-A3B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.8-27B
- MiniCPM-V 4.7 35B-A3B vs Qwen3.8-Flash-Next
- MiniCPM-V 4.7 35B-A3B vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-Coder-Next
- MiniCPM-V 4.7 35B-A3B vs Qwen3-Omni-30B-A3B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-VL-2B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-VL-30B-A3B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-VL-32B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-VL-4B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwen3-VL-8B-Instruct
- MiniCPM-V 4.7 35B-A3B vs Qwopus3.8-27B-Flash-V2
- MiniCPM-V 4.7 35B-A3B vs Recursive Flint
- MiniCPM-V 4.7 35B-A3B vs Ripple-65B Preview
- MiniCPM-V 4.7 35B-A3B vs SenseNova-Loop-9B-Preview
- MiniCPM-V 4.7 35B-A3B vs SmolLM3-3B
- MiniCPM-V 4.7 35B-A3B vs Spark-X2.6-4B
- MiniCPM-V 4.7 35B-A3B vs Step 3.7 Flash
- MiniCPM-V 4.7 35B-A3B vs Swift 1.5 Qwen3.8-27B
- MiniCPM-V 4.7 35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next
- MiniCPM-V 4.7 35B-A3B vs ThinkingCap (Qwen3.8 27B)
- MiniCPM-V 4.7 35B-A3B vs Baidu Unlimited-OCR-2
- MiniCPM-V 4.7 35B-A3B vs WeVisOne-VL-2B
- MiniCPM-V 4.7 35B-A3B vs WeVisOne-VL-4B
- MiniCPM-V 4.7 35B-A3B vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minicpm-v-4-7-35b-a3b.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/minicpm-v-4-7-35b-a3b.json - From a terminal
anchor compare internvl3-5-gpt-oss-20b-a4b-preview minicpm-v-4-7-35b-a3b(the CLI) - Over MCP
compare_tools {"a": "internvl3-5-gpt-oss-20b-a4b-preview", "b": "minicpm-v-4-7-35b-a3b"}at/mcp, no key