Qwen: Qwen3 235B A22B Thinking 2507 vs Google: Gemma 3 4B
Head-to-head API cost, context, and performance comparison. Synced at 6:43:38 PM.
Executive Summary
When evaluating Qwen: Qwen3 235B A22B Thinking 2507 against Google: Gemma 3 4B, the pricing structure is a key differentiator. Google: Gemma 3 4B is approximately 25% more cost-effective per 1 million tokens overall.
However, when looking at raw reasoning capabilities, Qwen: Qwen3 235B A22B Thinking 2507 leads with a statistical ELO score of 1046. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3 235B A22B Thinking 2507, provided their budget allows for the API burn rate.
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Raw Technical comparison
Verdict
If you are looking for pure performance and capability, Qwen: Qwen3 235B A22B Thinking 2507 is statistically superior. However, if API burn rate is the primary concern, Google: Gemma 3 4B wins out aggressively in pricing.
People Also Ask
Is Qwen: Qwen3 235B A22B Thinking 2507 cheaper than Google: Gemma 3 4B?
No. Google: Gemma 3 4B is the more cost-effective model, operating at a lower price point per 1 million tokens.
Which model has the larger context window?
The Qwen: Qwen3 235B A22B Thinking 2507 model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.