# DeepSeek-V3.2 vs MiniCPM-V 4.7 1B (slim)

> MiniCPM-V 4.7 1B scores 61 (C) to DeepSeek-V3.2's 58.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

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MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.

- DeepSeek-V3.2: C 58.6, rank #102 of 160 open-weight models · https://www.anchorterminal.com/tools/deepseek-v3-2.min.md
- MiniCPM-V 4.7 1B: C 61, rank #76 of 160 open-weight models · https://www.anchorterminal.com/tools/minicpm-v-4-7-1b.min.md
- DeepSeek-V3.2, good for Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider
- MiniCPM-V 4.7 1B, good 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 60; Risk, 55 against 50; Agent interface, 70 against 60; Documentation and upkeep, 48 against 34.

| Category | DeepSeek-V3.2 | MiniCPM-V 4.7 1B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 95 |
| Risk (20%) | 50 | 55 |
| Agent interface (10%) | 60 | 70 |
| Documentation and upkeep (10%) | 34 | 48 |

| Fact (where they differ) | DeepSeek-V3.2 | MiniCPM-V 4.7 1B |
| --- | --- | --- |
| Vendor | DeepSeek | OpenBMB |
| Licence | MIT | Apache-2.0 |
| Last release | 2025-12-01 | 2026-10-30 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Reach, MiniCPM-V 4.7 1B +35: DeepSeek-V3.2 60 (Memory earns nothing, because the only build from DeepSeek or a runtime's library is the 689.5 GB FP8 release, which needs about 827 GB with the fifth added.); 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.)
- Documentation and upkeep, MiniCPM-V 4.7 1B +14: DeepSeek-V3.2 34 (The model card earns 14 when read with DeepSeek's own V3.2 model card PDF, which adds intended use and a parameter count, leaving languages and a knowledge cut-…); 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 p…)
- Agent interface, MiniCPM-V 4.7 1B +10: DeepSeek-V3.2 60 (The chat template earns 10, as the format exists only as Python code to run.); MiniCPM-V 4.7 1B 70 (Chat template 20, chat_template.jinja in the repository, 7,249 characters.)
- Risk, MiniCPM-V 4.7 1B +5: DeepSeek-V3.2 50 (File safety earns 15, safetensors only but 10 off because prompts are built by running DeepSeek's Python from the repository.); 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 r…)