readygpu

Gemma 4 26B-A4B

25.8B total, 4B active · 256k context · apache-2.0 · released 2026-03-11

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What to run it on in Germany

Fully in memory at 128k context, priced at retailers today.

Something we price holds it fully in memory, but none reaches 15 tok/s, our bar for recommending it. The table below has the speeds.

All hardware that runs it

Everything we price, best value first. Two cards split the model by layers.

HardwareQuantFitsDecodePricetok/s per 1,000
NVIDIA GeForce RTX 3090UD-Q4_K_Mfits63 tok/s––
NVIDIA GeForce RTX 5090Q8_0fits95 tok/s––
Mac Studio M4 Max 128GBQ8_0fits30 tok/s––
NVIDIA GeForce RTX 4090UD-Q4_K_Mfits68 tok/s––
Mac mini M4 Pro 64GBQ8_0fits15 tok/s––
AMD Radeon RX 7900 XTXUD-Q4_K_Mfits57 tok/s––
Framework Desktop Ryzen AI Max+ 395 128GBQ8_0fits12 tok/s––
Mac Studio M3 Ultra 512GBQ8_0fits45 tok/s––
NVIDIA DGX Spark 128GBQ8_0fits14 tok/s––
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBQ8_0fits12 tok/s––
Mac Studio M3 Ultra 256GBQ8_0fits45 tok/s––
Mac mini M4 Pro 48GBQ8_0fits15 tok/s––
Mac Studio M4 Max 64GBQ8_0fits30 tok/s––
Mac Studio M3 Ultra 96GBQ8_0fits45 tok/s––
NVIDIA RTX PRO 6000 BlackwellQ8_0fits95 tok/s––
AMD Radeon AI PRO R9700Q8_0fits30 tok/s––
ASUS Ascent GX10 128GBQ8_0fits14 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBQ8_0fits12 tok/s––
Mac mini M4 32GBUD-Q4_K_Mfits9 tok/s––
NVIDIA GeForce RTX 3090 TiUD-Q4_K_Mfits68 tok/s––
Intel Arc Pro B60UD-Q4_K_Mfits23 tok/s––
NVIDIA Tesla P40UD-Q4_K_Mfits23 tok/s––
NVIDIA GeForce RTX 5070 TiUD-Q4_K_Moffload18 tok/s––
NVIDIA GeForce RTX 5060 Ti 16GBUD-Q4_K_Moffload15 tok/s––
NVIDIA GeForce RTX 3060 12GBUD-Q4_K_Moffload10 tok/s––
AMD Radeon RX 9070 XTUD-Q4_K_Moffload16 tok/s––
NVIDIA GeForce RTX 4060 Ti 16GBUD-Q4_K_Moffload12 tok/s––
NVIDIA GeForce RTX 5080UD-Q4_K_Moffload19 tok/s––
NVIDIA GeForce RTX 4070 Ti SuperUD-Q4_K_Moffload17 tok/s––
NVIDIA GeForce RTX 5070UD-Q4_K_Moffload11 tok/s––
AMD Radeon RX 9060 XT 16GBUD-Q4_K_Moffload12 tok/s––
NVIDIA GeForce RTX 4070 SuperUD-Q4_K_Moffload11 tok/s––
NVIDIA GeForce RTX 4080 SuperUD-Q4_K_Moffload18 tok/s––
AMD Radeon RX 7800 XTUD-Q4_K_Moffload16 tok/s––
AMD Radeon RX 7900 XTUD-Q4_K_Moffload36 tok/s––
Intel Arc B580UD-Q4_K_Moffload9 tok/s––
AMD Radeon RX 7600 XTUD-Q4_K_Moffload11 tok/s––
NVIDIA GeForce RTX 3080 10GBUD-Q4_K_Moffload9 tok/s––
Intel Arc A770 16GBUD-Q4_K_Moffload13 tok/s––

1 other card or machine we price cannot hold it at this context.

Memory needed

Weights, KV cache and runtime buffers at each context length (KV cache at fp16).

QuantFile@8k@32k@64k@128k
UD-Q4_K_Mgguf15.8 GB16.9 GB17.5 GB18.3 GB19.9 GB
mlx-4bitmlx14.3 GB15.4 GB16.0 GB16.8 GB18.4 GB
UD-Q5_K_Mgguf19.7 GB20.8 GB21.4 GB22.2 GB23.8 GB
UD-Q6_Kgguf21.6 GB22.7 GB23.3 GB24.1 GB25.7 GB
Q8_0gguf25.0 GB26.1 GB26.7 GB27.5 GB29.2 GB
mlx-8bitmlx26.0 GB27.1 GB27.7 GB28.6 GB30.2 GB

Run it

Copy a command for the runtime you use.

  • UD-Q4_K_M
    • Ollamaollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M
    • LM Studiolms get unsloth/gemma-4-26B-A4B-it-GGUF@ud-q4_k_m
    • llama.cppllama-server -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q4_K_M
  • mlx-4bit
    • LM Studiolms get mlx-community/gemma-4-26B-A4B-it-4bit
    • MLXmlx_lm.server --model mlx-community/gemma-4-26B-A4B-it-4bit
  • UD-Q5_K_M
    • Ollamaollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q5_K_M
    • LM Studiolms get unsloth/gemma-4-26B-A4B-it-GGUF@ud-q5_k_m
    • llama.cppllama-server -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q5_K_M
  • UD-Q6_K
    • Ollamaollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q6_K
    • LM Studiolms get unsloth/gemma-4-26B-A4B-it-GGUF@ud-q6_k
    • llama.cppllama-server -hf unsloth/gemma-4-26B-A4B-it-GGUF:UD-Q6_K
  • Q8_0
    • Ollamaollama run hf.co/unsloth/gemma-4-26B-A4B-it-GGUF:Q8_0
    • LM Studiolms get unsloth/gemma-4-26B-A4B-it-GGUF@q8_0
    • llama.cppllama-server -hf unsloth/gemma-4-26B-A4B-it-GGUF:Q8_0
  • mlx-8bit
    • LM Studiolms get mlx-community/gemma-4-26B-A4B-it-8bit
    • MLXmlx_lm.server --model mlx-community/gemma-4-26B-A4B-it-8bit