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GoogleGemma 4 26B A4BVSMetaLlama-3.1 8B

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend Gemma 4 26B A4B for superior reasoning capability, or Llama-3.1 8B 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 Llama-3.1 8B 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 Llama-3.1 8B scored 30.4% (+51.9% gap).
  • Coding Performance: Evaluated on different benchmarks. Gemma 4 26B A4B scored 77.1% on LiveCodeBench (scripting single-file apps or clearly defined functions), while Llama-3.1 8B scored 72.6% on HumanEval (basic standalone code completion and simple functions).
  • Hardware Footprint: Gemma 4 26B A4B is a 25.2B parameter model requiring more VRAM, while Llama-3.1 8B is a 8B parameter model.
  • Was this recommendation helpful?
    Model Specs

    Gemma 4 26B A4B

    Open Source

    Benchmarks & Scores

    Coding (live-code-bench)
    77.1%

    scripting single-file apps or clearly defined functions

    Reasoning (gpqa-diamond)Winner (+51.9%)
    82.3%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    Self HostLocal execution (zero API fees)
    Context WindowLarger
    262.14k tokens
    Model Specs

    Llama-3.1 8B

    Open Source

    Benchmarks & Scores

    Coding (human-eval)
    72.6%

    basic standalone code completion and simple functions

    Reasoning (gpqa-diamond)
    30.4%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    Self HostLocal execution (zero API fees)
    Context Window
    131.07k tokens

    Frequently Asked Questions about Gemma 4 26B A4B vs Llama-3.1 8B

    For coding tasks, Gemma 4 26B A4B scores 77.1% on live-code-bench (scripting single-file apps or clearly defined functions), while Llama-3.1 8B scores 72.6% on human-eval (basic standalone code completion and simple functions).

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