How much memory does Gemma 4 26B-A4B need?
About 17 GB at Q4_K_M with an 8K context. It runs on a Mac with 24 GB of unified memory or more.
Try other settings in the calculatorMemory by quantization and context
Total memory: weights, KV cache in F16 and about 1 GB of buffers. Under each total, the smallest Mac that can run it with the default GPU memory limit.
| Quantization | 8K context | 32K context | 128K context |
|---|---|---|---|
| Q3_K_M | 14 GB24 GB Mac | 15 GB24 GB Mac | 19 GB32 GB Mac |
| Q4_K_M | 17 GB24 GB Mac | 18 GB32 GB Mac | 22 GB32 GB Mac |
| Q5_K_M | 20 GB32 GB Mac | 21 GB32 GB Mac | 25 GB48 GB Mac |
| Q6_K | 23 GB32 GB Mac | 24 GB32 GB Mac | 28 GB48 GB Mac |
| Q8_0 | 29 GB48 GB Mac | 30 GB48 GB Mac | 34 GB48 GB Mac |
| F16 | 53 GB96 GB Mac | 54 GB96 GB Mac | 58 GB96 GB Mac |
About the model
- Parameters
- 25.81B
- Type
- Mixture of experts, 128 experts
- Attention
- sliding window plus full attention
- KV cache, F16
- 0.5 GB at 8K, 5.6 GB at 128K
- On Hugging Face
- google/gemma-4-26B-A4B-it
Some layers only look at the last 1,024 tokens, so their part of the cache stops growing. The full-attention layers still grow with context. As a mixture-of-experts model it loads every expert into memory, so memory follows the total parameter count, while speed follows the smaller number of active parameters.
Questions
How much memory does Gemma 4 26B-A4B need?
About 17 GB at Q4_K_M with an 8K context: 16 GB of weights, 0.5 GB of KV cache and about 1 GB of buffers. At 32K context it needs about 18 GB.
Can Gemma 4 26B-A4B run on a Mac?
Yes. At Q4_K_M with an 8K context it fits on a Mac with 24 GB of unified memory or more, using the default GPU memory limit of about three quarters.
How big is the Gemma 4 26B-A4B KV cache?
About 0.5 GB at 8K tokens and 5.6 GB at 128K tokens with an F16 cache. Its attention design: sliding window plus full attention.
Other models
- Gemma 4 12B
- gpt-oss 20B
- Qwen3.8 27B
- GLM-4.7 Flash
- Gemma 4 31B
- Qwen3.6 35B-A3B
- gpt-oss 120B
- Mistral Medium 3.5
- Qwen3.8 Flash Next
- DeepSeek V4 Flash
- GLM-5.3
- DeepSeek V4 Pro
- Kimi K3
Data read from Hugging Face on 2026-11-09. These are estimates; benchmarks on this site report measured memory. How the estimate works. Compare all models in the model fit chart.
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