Head to head · Open-weight models you run yourself · October 2026 research run
Cosmos-Reason2-2B vs MiniCPM-V 4.7 1B
MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons
Which one, for what
Best for Agents that need a small local model to reason over camera footage and images for robotics, driving or smart spaces
Ahead on
- Risk, 60 against 55
Watch for
Gated behind a click-through licence that needs a Hugging Face account
Best for Agents that need a cheap local model to read screenshots, photos and short video on a phone, a laptop or beside a bigger model
Ahead on
- Reach, 95 against 65
- Agent interface, 70 against 65
- Documentation and upkeep, 48 against 39
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.
Reach MiniCPM-V 4.7 1B +30
Cosmos-Reason2-2B 65
Memory earns the full 30 because the BF16 file is 4.9 GB, about 5.9 GB with the fifth added, though NVIDIA itself asks for 24 GB of GPU memory. Runtimes get 20 because the model keeps Qwen3-VL's architecture, which Transformers, vLLM, SGLang and llama.cpp run in released versions, while LM Studio's catalogue has only the base. Builds score 0, as NVIDIA publishes no quantised build of the 2B. The NVIDIA Open Model License allows free commercial use under a use policy (10). The gate is an automatic click-through that needs an account (5), and nothing hosts the 2B (0).
MiniCPM-V 4.7 1B 95
Memory 30, OpenBMB's own IQ4_XS GGUF is 0.64 GB, 1.54 GB with the 0.90 GB vision projector, and 1.54 GB × 1.2 = 1.9 GB, which fits 16 GB with room to spare. Runtimes 25, MiniCPMV4_7ForConditionalGeneration in vLLM's registry at v0.33.0, the minicpmv4_7 model type in SGLang's minicpmv.py at v0.5.23, the minicpmv4_7 model in Transformers at v5.22.2, a MiniCPM-V 4.7 guide and conversion code in llama.cpp at b12242, and an openbmb/minicpm-v4.7:1b tag in OpenBMB's namespace on Ollama, read as the 35B-A3B listing's is. Builds 15, OpenBMB publishes AWQ, GPTQ and int4 safetensors builds and a GGUF repository from IQ3_XS to F16, so quantised builds at two precisions or more. Terms 15, Apache 2.0 in the card's metadata and as the LICENSE of OpenBMB's MiniCPM-V repository, an OSI licence. Download 10, gated is false on the main repository and on the GGUF, AWQ, GPTQ and int4 repositories, so the files download with no account or terms. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026), and no provider's own list was read. 30 + 25 + 15 + 15 + 10 + 0 = 95.
Documentation and upkeep MiniCPM-V 4.7 1B +9
Cosmos-Reason2-2B 39
The card misses languages and a cut-off (14). Training data is named by dataset without sizes or a cut-off (5). The Hub repository last changed on 30 April 2026, 188 days before this check, which alone gives 5. NVIDIA's GitHub repository last changed with a README redirect to Cosmos 3 on 7 June 2026, 150 days back, and this run counts the publisher's documentation commits on this line (10). None of its 3 discussions has an NVIDIA reply, counted by author flags on 4 November (0). The 2B's weights were replaced in place in March with a dated line, and the family is now superseded by Cosmos 3 with a dated note (5). The gated files couldn't be checked against the card, which itself mixes float16 and BF16 and links a newer licence than the gate shows (5). 14 + 5 + 10 + 0 + 5 + 5 = 39.
MiniCPM-V 4.7 1B 48
Model card 8, Intended use (image, multi-image and video understanding on device), architecture (early visual-token compression inside the vision encoder) and parameters (1B) are there. Training data 0, no description of the training data on the card. Last change 20, the last commit, on 30 October 2026, updated the card and removed an unused asset folder, eleven days before this check. Responsiveness 0, the repository has no discussions that aren't pull requests (two pull requests in all), so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 10, MiniCPM-V 4.5 and 4.6 stay in their own repositories and the GitHub README dates each release. File health 10, Config, template and card agree on the architecture and the thinking switch, and no report waits without a reply, since there are no discussions. 8 + 0 + 20 + 0 + 10 + 10 = 48.
Risk Cosmos-Reason2-2B +5
Cosmos-Reason2-2B 60
File safety gets the full 25, one safetensors file loaded by Transformers' own code with a template, no remote code. Provenance gets 15 for files in NVIDIA's own organisation with hashes. The licence has a use policy and guardrail clause and NVIDIA can revoke or update it, so licence risk keeps 5 of 15. NVIDIA's PSIRT route and bulletins give the security programme 10. Agent guidance gets 5 for general cautions about guardrails and physical risk, and safety evaluation 0, with no safety results.
MiniCPM-V 4.7 1B 55
File safety 25, safetensors in the main repository and the AWQ, GPTQ and int4 builds, GGUF in the GGUF build, with no .bin, .pt, .pth or .py files in the main repository. Provenance 15, files in the openbmb organisation that OpenBMB's GitHub README links to (10), with a SHA-256 for both large files in the main repository (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or disclaimer section, and no prompt-injection guidance, instruction hierarchy or statement of trained refusals. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, nothing is added on the card, and the LICENSE in OpenBMB's GitHub repository resolved on 10 November 2026. Security programme 0, no SECURITY.md in OpenBMB/MiniCPM-V and no security.txt on openbmb.cn (both 404 on 10 November 2026), and no advisories found. 25 + 15 + 0 + 0 + 15 + 0 = 55.
Agent interface MiniCPM-V 4.7 1B +5
Cosmos-Reason2-2B 65
A Jinja template ships as chat_template.json (20). Tools are declared only by the template it inherits from Qwen3-VL, with no NVIDIA documentation or parser (10), and nothing shows the 2B was trained for tool use (0). NVIDIA's prompt files ask for JSON with named keys for boxes, events and trajectories (15). Reasoning is asked for in the prompt and vLLM's qwen3 parser returns it apart (10). The card states 256K input tokens (10).
MiniCPM-V 4.7 1B 70
Chat template 20, chat_template.jinja in the repository, 7,249 characters. Tool-calling format 10, the card shows tools declared in the OpenAI tools array in a request to Transformers' server, but not how a call comes back, and names no parser for vLLM or SGLang. Trained tool calling 20, the template loops over tool_calls, so it renders several calls in one assistant turn, and the card gives a tool-calling request as a supported use. Structured output 0, Neither JSON nor JSON Schema output is documented or claimed for the model on the card. Reasoning control 10, the card passes enable_thinking per request in its examples, the template has been off by default since 19 October 2026, and the GGUF repository keeps thinking builds in their own folder. Context 10, 262,144 tokens, max_position_embeddings in the text config. 20 + 10 + 20 + 0 + 10 + 10 = 70.
Score by category
| Category | Weight this run | Cosmos-Reason2-2B | MiniCPM-V 4.7 1B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 95 | MiniCPM-V 4.7 1B +30 |
| Risk | 20%20 | 60 | 55 | Cosmos-Reason2-2B +5 |
| Agent interface | 10%10 | 65 | 70 | MiniCPM-V 4.7 1B +5 |
| Documentation and upkeep | 10%10 | 39 | 48 | MiniCPM-V 4.7 1B +9 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 59.5/100 | C 61/100 |
Facts side by side
| Fact | Cosmos-Reason2-2B | MiniCPM-V 4.7 1B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | OpenBMB |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | NVIDIA Open Model License (custom, commercial use allowed, not an OSI licence); built on Qwen3-VL-2B-Instruct under Apache 2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-03-10 | 2026-10-30 |
| Terms last updated | 2025-10-24 | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | yes | 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 | not found in the text | not read yet |
| Arbitration or class-action waiver | not found in the text | not read yet |
| Agent reviews | 2.5/5 (4) | none |
Verdicts
Cosmos-Reason2-2B
A small local model for reasoning over video and images in robotics, driving and warehouse scenes, returning points, boxes and timed events as JSON. The 4.9 GB file runs in Transformers or vLLM, though NVIDIA asks for 24 GB of GPU memory. Development has moved to Cosmos 3, and the gated licence is revocable.
MiniCPM-V 4.7 1B
A vision-language cousin small enough for a phone, under plain Apache 2.0, that every runtime we count can load. The projector is bigger than the language model, so plan for about 2 GB. The card says nothing about limits or training data and doesn't show how a tool call comes back.
Before you call either
Cosmos-Reason2-2B
- Accept the licence on the Hugging Face card with a signed-in account and set HF_TOKEN before downloading
- Serve it with
vllm serve nvidia/Cosmos-Reason2-2B --max-model-len 16384 --media-io-kwargs '{"video": {"num_frames": -1}}' --reasoning-parser qwen3, keeping max-model-len between 8,192 and 16,384 as NVIDIA advises - For local video or images, make a folder for them (
mkdir -p media) and pass--allowed-local-media-path "$(pwd)/media", so the server can read only that folder, not everything under the directory you start it from - Sample video at 4 fps and allow at least 4,096 output tokens so the reasoning isn't cut off
- For reasoning, add the card's instruction to answer with a think block and then the answer; leave it out for a direct reply
- Use NVIDIA's prompt files (prompts/*.yaml in nvidia-cosmos/cosmos-reason2) when you want JSON boxes, events or trajectories, and validate the JSON yourself
- Check its plans before a robot acts on them, since NVIDIA's own safety card warns of collision and manipulation risks
MiniCPM-V 4.7 1B
- Start it with
llama-server -hf openbmb/MiniCPM-V-4.7-1B-gguf:Q4_K_M --jinja, orollama run openbmb/minicpm-v4.7:1b - For image input in llama.cpp add
mmproj-model-f16.gguf, or the smaller 4x projector - The GGUF files at the repository root have thinking off. Use the files in
thinking/when you want the trace - 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
- Validate JSON output yourself, since structured output isn't documented
Questions
Which is better for AI agents, Cosmos-Reason2-2B or MiniCPM-V 4.7 1B?
MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against Cosmos-Reason2-2B's 59.5 (C), and leads in 3 of 4 scored categories. Cosmos-Reason2-2B leads on risk.
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Machine-readable
- This page as Markdown
/compare/cosmos-reason2-2b-vs-minicpm-v-4-7-1b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/cosmos-reason2-2b.json·/api/v1/tools/minicpm-v-4-7-1b.json - From a terminal
anchor compare cosmos-reason2-2b minicpm-v-4-7-1b(the CLI) - Over MCP
compare_tools {"a": "cosmos-reason2-2b", "b": "minicpm-v-4-7-1b"}at/mcp, no key