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Gemma 4 26B A4B

Gemma 4 MoE flagship-for-workstations: 26B total with ~4B active parameters. 256K context and excellent quality-per-watt for local inference. Apache 2.0.

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Parameters
26B (A4B active)
Minimum RAM
24 GB
Model size
16 GB
Quantization
Q4_K_M

Can Gemma 4 26B A4B run locally?

Gemma 4 26B A4B is best suited for power-user machines with 32 GB RAM. LocalClaw recommends Q4_K_M as the default quantization, with at least 24 GB RAM.

Search term for LM Studio or compatible runtimes: gemma-4-26b-a4b-it

Hugging Face repository: google/gemma-4-26B-A4B-it

chatcodereasoningpowermultimodalgeneral

Strengths

  • Excellent quality-per-watt
  • Large-model quality with reduced active compute
  • 256K context
  • Strong coding and reasoning

Limitations

  • Needs workstation-class RAM/VRAM for comfortable local inference

Best use cases

  • Advanced assistant
  • Agent workflows
  • Coding support
  • Research and analysis

Benchmarks

Speed: 7/10

Quality: 9/10

Coding: 8/10

Reasoning: 9/10

Technical details

Developer: Google DeepMind

License: Apache 2.0

Context window: 262,144 tokens

Architecture: Mixture-of-Experts style Gemma 4 (26B total, ~4B active)

Released: 2026-03

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