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Mistral: Mistral Large 3 2512 vs Qwen: Qwen3.5-122B-A10B

Head-to-head API cost, context, and performance comparison. Synced at 11:21:58 AM.

Executive Summary

When evaluating Mistral: Mistral Large 3 2512 against Qwen: Qwen3.5-122B-A10B, the pricing structure is a key differentiator. Mistral: Mistral Large 3 2512 is approximately 15% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Qwen: Qwen3.5-122B-A10B leads with a statistical ELO score of 1120. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3.5-122B-A10B, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Mistral: Mistral Large 3 2512
Qwen: Qwen3.5-122B-A10B
Performance (ELO)
1120
1120
Input Cost / 1M
$0.50
$0.26
Output Cost / 1M
$1.50
$2.08
Context Window
262,144 tokens
262,144 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 Large 3 2512 wins out aggressively in pricing.

People Also Ask

Is Mistral: Mistral Large 3 2512 cheaper than Qwen: Qwen3.5-122B-A10B?

Yes. Mistral: Mistral Large 3 2512 is cheaper for both input and output generation compared to Qwen: Qwen3.5-122B-A10B. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

Both models offer an identical context window of 262,144 tokens.

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