LLM Comparison
DiffusionGemma vs MiniCPM
Side-by-side specs, pricing & capabilities · Updated September 2026
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 29 | |
| Family | Gemma | MiniCPM |
| Status | Current | Current |
| Release Date | Jun 2026 | — |
| Context Window | 256K tokens | 128K tokens |
| Input Price | — | — |
| Output Price | — | — |
| Pricing Notes | Google publishes open weights for local deployment. A hosted API price has not been verified; hosting and infrastructure costs depend on the provider or deployment. | 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 | textvisioncodereasoninglocal-inference | textcodereasoninglocal-inference |
| Training Cutoff | — | Not publicly specified in queued source |
| Max Output | — | 33K tokens |
| API Identifier | google/diffusiongemma-26b-a4b-it | OpenBMB/MiniCPM |
| Benchmarks | ||
| MMLU Pro | 77.6official-google-model-card | — |
| GPQA Diamond | 73.2official-google-model-card | — |
| LiveCodeBench v6 | 69.1official-google-model-card | — |
| MMMLU | 81.5official-google-model-card | — |
| HLE no tools | 11official-google-model-card | — |
| 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 DiffusionGemma | View MiniCPM | |
DiffusionGemma
DiffusionGemma is Google DeepMind’s experimental open-weights text-diffusion model based on Gemma 4 26B A4B. It uses discrete diffusion and parallel canvas denoising to trade some benchmark quality for much faster local generation on dedicated GPUs.
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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