LLM Comparison
DiffusionGemma vs Maple-Preview
Side-by-side specs, pricing & capabilities · Updated September 2026
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2/6 models| Organization | ||
| OpenTools Score | 29 | 45 |
| Family | Gemma | Maple |
| Status | Current | Current |
| Release Date | Jun 2026 | Aug 2026 |
| Context Window | 256K tokens | 131K 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-source model card; no hosted API pricing found in the official source. Local inference costs depend on user hardware and runtime. |
| Capabilities | textvisioncodereasoninglocal-inference | textreasoningcodeon-device-inference |
| API Identifier | google/diffusiongemma-26b-a4b-it | deepgrove/maple-preview |
| Benchmarks | ||
| MMLU Pro | 77.6official-google-model-card | — |
| GPQA Diamond | 73.2official-google-model-card | 73.5DeepGrove model card |
| LiveCodeBench v6 | 69.1official-google-model-card | 75.1DeepGrove model card |
| MMMLU | 81.5official-google-model-card | — |
| HLE no tools | 11official-google-model-card | — |
| AIME 2026 | — | 87.5DeepGrove model card |
| HMMT 2026 | — | 78.8DeepGrove model card |
| View DiffusionGemma | View Maple-Preview | |
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.
DeepGrove
Maple-Preview
Maple-Preview is DeepGrove’s open-source 20B-A1B ternary-weight reasoning LLM for efficient on-device inference. The model card reports 20.2B total parameters, 1.49B active parameters, a 131,072-token context window, and 5.31 GB checkpoint size. The model card specifies 131,072 tokens of context but does not establish a separate maximum output-token limit.
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