In r LocalLLaMA, Gemma 4 is being benchmarked as unusually strong for its size and cost, but builders also report practical issues like llama cpp consuming system RAM on long contexts and mixed results on niche coding tasks.
Gemma 4 just casually destroyed every model on our leaderboard except Opus 4.6 and GPT-5.2.
31B params, $0.20/run Tested Gemma 4 (31B) on our benchmark.
llama.cpp was using 63GB
Gemma 4 31B with 32GB of VRAM and 64GB of DDR5
Gemma 4 didn't really work for my use case. Which is diagnosing PLC Code. Qwen-Coder-Next still does best job for that.
31B params, $0.20/run Tested Gemma 4 (31B) on our benchmark. Genuinely did not expect this.
It outperforms GPT-5.2 ($4.43/run), Gemini 3 Pro ($2.95/run), Sonnet 4.6 ($7.90/run)
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