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Qwen: Qwen3.5-35B-A3B vs DeepSeek: DeepSeek V3.1

Head-to-head API cost, context, and performance comparison. Synced at 2:34:16 PM.

Executive Summary

When evaluating Qwen: Qwen3.5-35B-A3B against DeepSeek: DeepSeek V3.1, the pricing structure is a key differentiator. DeepSeek: DeepSeek V3.1 is approximately 38% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, DeepSeek: DeepSeek V3.1 leads with a statistical ELO score of 1434. For tasks involving complex logic, coding, or instruction-following, developers might prefer DeepSeek: DeepSeek V3.1, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Qwen: Qwen3.5-35B-A3B
DeepSeek: DeepSeek V3.1
Performance (ELO)
1434
1434
Input Cost / 1M
$0.16
$0.15
Output Cost / 1M
$1.30
$0.75
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, DeepSeek: DeepSeek V3.1 wins out aggressively in pricing.

People Also Ask

Is Qwen: Qwen3.5-35B-A3B cheaper than DeepSeek: DeepSeek V3.1?

No. DeepSeek: DeepSeek V3.1 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: Qwen3.5-35B-A3B model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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