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LLMs ·

DiffusionGemma 26B-A4B IT

Parameters
26B (4.0B active)
Architecture
Mixture of experts
Max context
256K tokens
License
apache-2.0
Released
2026-06

How to run it

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/unsloth/diffusiongemma-26B-A4B-it-GGUF (opens in a new tab)

ollama run hf.co/unsloth/diffusiongemma-26B-A4B-it-GGUF

Original weights · Hugging Face

Full-precision files from Google, for fine-tuning, vLLM, Transformers.

huggingface.co/google/diffusiongemma-26B-A4B-it (opens in a new tab)

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

Memory needed

Weights plus KV cache and runtime overhead. Leave a little extra free for the operating system and other apps.

KV cache: block-diffusion model: generates blocks of tokens in parallel, so real speed can differ from this autoregressive estimate.

Quantization Quality Weights Total at 8K context Total at 32K context Download
Q2_K Low 10.3 GB 11.3 GB 12.5 GB GGUF files (opens in a new tab)
Q3_K_M Low 12.7 GB 13.7 GB 14.9 GB GGUF files (opens in a new tab)
Q4_K_M Good 15.8 GB 16.8 GB 18.0 GB GGUF (opens in a new tab)
Q5_K_M High 18.3 GB 19.3 GB 20.5 GB GGUF (opens in a new tab)
Q6_K High 21.2 GB 22.2 GB 23.4 GB GGUF (opens in a new tab)
Q8_0 Very high 27.4 GB 28.4 GB 29.6 GB GGUF (opens in a new tab)
F16 Full 51.6 GB 52.6 GB 53.9 GB GGUF (opens in a new tab) Original weights (opens in a new tab)

Best hardware for DiffusionGemma 26B-A4B IT

The least expensive GPU in our catalog that runs it without offloading is the Intel Arc B580 (launch price $249) at Q2_K.

Grade · points Hardware Quant Memory Speed Fit
89 ptsExcellent (S) · 89 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q6_K 23.8 GB / 32.0 GB 191 tok/s Runs well
88 ptsExcellent (S) · 88 of 100 points: Model quality 35.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.8/15 NVIDIA RTX PRO 6000 Blackwell F16 57.4 GB / 96.0 GB 64.5 tok/s Runs well
88 ptsExcellent (S) · 88 of 100 points: Model quality 34.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q6_K 23.4 GB / 24.0 GB 88.0 tok/s Tight fit
88 ptsExcellent (S) · 88 of 100 points: Model quality 34.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q6_K 23.4 GB / 24.0 GB 99.6 tok/s Tight fit
88 ptsExcellent (S) · 88 of 100 points: Model quality 34.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q6_K 23.4 GB / 24.0 GB 107 tok/s Tight fit
87 ptsExcellent (S) · 87 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.5/15 Apple M4 Max (64 GB) Q6_K 26.0 GB / 48.0 GB 50.1 tok/s Runs well
86 ptsExcellent (S) · 86 of 100 points: Model quality 34.7/45, Memory fit 25.0/25, Speed 14.4/15, Memory use 12.5/15 Apple M1 Max (64 GB) Q6_K 26.0 GB / 48.0 GB 36.7 tok/s Runs well
85 ptsExcellent (S) · 85 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 14.2/15, Memory use 12.6/15 Apple M4 Pro (48 GB) Q4_K_M 19.6 GB / 36.0 GB 36.1 tok/s Runs well
83 ptsGreat (A) · 83 of 100 points: Model quality 29.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 9070 XT Q3_K_M 14.5 GB / 16.0 GB 109 tok/s Tight fit
83 ptsGreat (A) · 83 of 100 points: Model quality 29.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Pro (24 GB) Q3_K_M 14.9 GB / 16.1 GB 46.6 tok/s Tight fit

Check it on your own hardware

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.