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Qwen: Qwen3 235B A22B Instruct 2507 vs Mistral: Mistral Small 3

Head-to-head API cost, context, and performance comparison. Synced at 2:36:03 PM.

Executive Summary

When evaluating Qwen: Qwen3 235B A22B Instruct 2507 against Mistral: Mistral Small 3, the pricing structure is a key differentiator. Mistral: Mistral Small 3 is approximately 24% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Mistral: Mistral Small 3 leads with a statistical ELO score of 1052. For tasks involving complex logic, coding, or instruction-following, developers might prefer Mistral: Mistral Small 3, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Qwen: Qwen3 235B A22B Instruct 2507
Mistral: Mistral Small 3
Performance (ELO)
1052
1052
Input Cost / 1M
$0.07
$0.05
Output Cost / 1M
$0.10
$0.08
Context Window
262,144 tokens
32,768 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Mistral: Mistral Small 3 wins out aggressively in pricing.

People Also Ask

Is Qwen: Qwen3 235B A22B Instruct 2507 cheaper than Mistral: Mistral Small 3?

No. Mistral: Mistral Small 3 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 Instruct 2507 model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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