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DeepSeek: R1 0528 vs Qwen: Qwen3.5-27B

Head-to-head API cost, context, and performance comparison. Synced at 11:20:13 AM.

Executive Summary

When evaluating DeepSeek: R1 0528 against Qwen: Qwen3.5-27B, the pricing structure is a key differentiator. Qwen: Qwen3.5-27B is approximately 33% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Qwen: Qwen3.5-27B leads with a statistical ELO score of 1120. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3.5-27B, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
DeepSeek: R1 0528
Qwen: Qwen3.5-27B
Performance (ELO)
1120
1120
Input Cost / 1M
$0.45
$0.20
Output Cost / 1M
$2.15
$1.56
Context Window
163,840 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, Qwen: Qwen3.5-27B wins out aggressively in pricing.

People Also Ask

Is DeepSeek: R1 0528 cheaper than Qwen: Qwen3.5-27B?

No. Qwen: Qwen3.5-27B 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: Qwen3.5-27B model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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