Alibaba Cloud (Qwen)Qwen3.6-35B-A3BVSGoogleGemma 4 31B
Our Take
We recommend selecting the model size (35B vs 30.7B) that fits best within your local hardware's VRAM constraints. Both models run locally for zero API costs and offer comparable performance.
▶WHY?
Benchmark Calculations & Evidence:
Reasoning Accuracy: Qwen3.6-35B-A3B scores 86% on reasoning compared to 84.3% for Gemma 4 31B.
Coding Performance: Evaluated on different benchmarks. Qwen3.6-35B-A3B scored 49.5% on SWE-bench Pro (complex codebases, multi-file repositories, and architectural planning), while Gemma 4 31B scored 80% on LiveCodeBench (scripting single-file apps or clearly defined functions).
Hardware Footprint: Qwen3.6-35B-A3B has 35B parameters, while Gemma 4 31B has 30.7B parameters.
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-pro)
49.5%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+1.7%)
86%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)
80%scripting single-file apps or clearly defined functions
Reasoning (gpqa-diamond)
84.3%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k tokensFrequently Asked Questions about Qwen3.6-35B-A3B vs Gemma 4 31B
For coding tasks, Qwen3.6-35B-A3B scores 49.5% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while Gemma 4 31B scores 80% on live-code-bench (scripting single-file apps or clearly defined functions).
Related Matchups
Explore similar comparisons for Qwen3.6-35B-A3B and Gemma 4 31B.
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.