GoogleGemma 4 12BVSGoogleGemma 4 26B A4B
Our Take
We recommend Gemma 4 26B A4B for superior reasoning capability, or Gemma 4 12B for faster local inference on smaller GPU hardware. While both models run locally for zero API costs, Gemma 4 26B A4B carries a larger parameter memory footprint. Choose Gemma 4 26B A4B if you have the VRAM to support it, or Gemma 4 12B for consumer-grade hardware compatibility.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Gemma 4 26B A4B scored 82.3%, while Gemma 4 12B scored 78.8% (+3.5% gap).
Coding Performance: Both models were evaluated on the LiveCodeBench benchmark. Gemma 4 26B A4B scored 77.1%, while Gemma 4 12B scored 72% (+5.1% gap).
Hardware Footprint: Gemma 4 26B A4B is a 25.2B parameter model requiring more VRAM, while Gemma 4 12B is a 11.95B parameter model.
Was this recommendation helpful?
Benchmarks & Scores
Coding (live-code-bench)
72%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)
78.8%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k tokensBenchmarks & Scores
Coding (live-code-bench)Winner (+5.1%)
77.1%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)Winner (+3.5%)
82.3%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k tokensFrequently Asked Questions about Gemma 4 12B vs Gemma 4 26B A4B
Gemma 4 26B A4B is better for coding tasks on this benchmark. It scores 77.1% on live-code-bench (scripting single-file apps or clearly defined functions) compared to Gemma 4 12B which scores 72%.
Related Matchups
Explore similar comparisons for Gemma 4 12B and Gemma 4 26B A4B.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.