LLM Comparison
DeepSeek V3.2 vs MiniCPM
Side-by-side specs, pricing & capabilities · Updated May 2026
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 53 156 | |
| Family | DeepSeek | MiniCPM |
| Status | Current | Current |
| Release Date | Dec 2025 | — |
| Context Window | 164K tokens | 128K tokens |
| Input Price | $0.26/M tokens | Free |
| Output Price | $0.42/M tokens | Free |
| Pricing Notes | Cache read: $0.1350/M tokens | Open-weight GitHub and Hugging Face model family. There is no fixed vendor API price; runtime cost depends on the host, hardware, or inference provider. |
| Capabilities | textcode | textcodereasoninglocal-inference |
| Training Cutoff | — | Not publicly specified in queued source |
| Max Output | 164K tokens | 33K tokens |
| API Identifier | deepseek/deepseek-v3.2 | OpenBMB/MiniCPM |
| Benchmarks | ||
| MMLU-Pro | 85deepseek | — |
| GPQA Diamond | 82.4deepseek | — |
| AIME 2025 | 93.1deepseek | — |
| LiveCodeBench | 83.3deepseek | — |
| SWE-bench Verified | 73.1deepseek | — |
| HLE | 25.1deepseek | — |
| BrowseComp | 51.4deepseek | — |
| MiniCPM-SALA standard benchmark average | — | 76.53official-github-readme |
| MiniCPM-SALA long-context average | — | 38.97official-github-readme |
| MiniCPM-SALA 2048K extrapolation score | — | 81.6official-github-readme |
| MiniCPM4.1 reasoning decoding speedup | — | 3official-github-readme |
| MiniCPM4 Jetson AGX Orin decoding speedup vs Qwen3-8B | — | 7official-github-readme |
| View DeepSeek V3.2 | View MiniCPM | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| MiniCPMCheapest | $0.00 | $0.00 | $0.00 | — |
| DeepSeek V3.2 | $0.26 | $0.21 | $0.47 | +0% |
DeepSeek
DeepSeek V3.2
DeepSeek V3.2 is a large language model from DeepSeek. Supports up to 163,840 token context window. Achieves 87.1% on MMLU. Available from $0.26/M input tokens.
OpenBMB
MiniCPM
MiniCPM is OpenBMB’s ultra-efficient open language-model family for edge and end-device deployment. The MiniCPM4 and MiniCPM4.1 lines focus on fast local reasoning, while MiniCPM-SALA extends the family toward sparse/linear attention and million-token context research.
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