API cost decision in 10 seconds

Qwen3.5-27B vs DeepSeek V3.2

Pick DeepSeek V3.2 for lower cost; pick Qwen3.5-27B only if the larger context window matters more.

Pricing data updated:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick DeepSeek V3.2 for lower cost; pick Qwen3.5-27B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $0.98 for Qwen3.5-27B, saving $0.53 (54.8% lower).

Cost-first pickDeepSeek V3.2
Context-first pickQwen3.5-27B
Sample savings$0.5354.8%
10x traffic gap$5.34

Qwen3.5-27B has more context, but DeepSeek V3.2 saves $0.53 on the standard workload. At 10x that traffic, the same price gap is about $5.34. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

DeepSeek V3.2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickQwen3.5-27BDeepSeek V3.2
Input-heavy / RAG5M input + 500K outputDeepSeek V3.2$1.75$1.45
Balanced workload1M input + 1M outputDeepSeek V3.2$1.76$0.63
Output-heavy chatbot1M input + 5M outputDeepSeek V3.2$8$2.14
Cheaper input Qwen3.5-27B $0.195 vs $0.252 / 1M

Qwen3.5-27B is $0.06 cheaper per 1M input tokens (22.6% lower; 1.29x difference).

Cheaper output DeepSeek V3.2 $1.56 vs $0.378 / 1M

DeepSeek V3.2 is $1.18 cheaper per 1M output tokens (75.8% lower; 4.13x difference).

Larger context Qwen3.5-27B 262.14K vs 131.07K

Qwen3.5-27B has 131.07K more context (2x larger).

Sample workload DeepSeek V3.2 $0.98 vs $0.44

DeepSeek V3.2 is $0.53 cheaper on the standard workload (54.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.5-27B Calculating… Estimated API cost
DeepSeek V3.2 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Qwen3.5-27B has the lower input price; DeepSeek V3.2 has the lower output price; Qwen3.5-27B offers the larger context window. For the 1M input plus 500K output sample, DeepSeek V3.2 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.98 for Qwen3.5-27B and $0.44 for DeepSeek V3.2.

Best Fit

Choose Qwen3.5-27B when you care most about lower input-token price, and larger context window.

Choose DeepSeek V3.2 when you care most about lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $0.98 for Qwen3.5-27B, saving $0.53 (54.8% lower).
  • DeepSeek V3.2 is $0.53 cheaper on the standard workload (54.8% lower).
  • Qwen3.5-27B is $0.06 cheaper per 1M input tokens (22.6% lower; 1.29x difference).
  • DeepSeek V3.2 is $1.18 cheaper per 1M output tokens (75.8% lower; 4.13x difference).
  • Qwen3.5-27B has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureQwen3.5-27B
(Qwen)
DeepSeek V3.2
(DeepSeek)
Input Price
prompt tokens per 1M
$0.195$0.252
Completion Price
per 1M tokens
$1.56$0.378
Sample Workload Cost
1M input + 500K output
$0.98$0.44
Context Window262.14K131.07K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionDeepSeek V3.2On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $0.98 for Qwen3.5-27B, saving $0.53 (54.8% lower).
High-volume input processingQwen3.5-27BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsDeepSeek V3.2Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3.5-27BA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

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Popular competitors
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Cheaper alternatives

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Larger context alternatives

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Qwen catalog

Review all tracked Qwen models before deciding whether this matchup is the right shortlist.

Open Qwen models

DeepSeek catalog

Check other DeepSeek models with comparable pricing, context, or release timing.

Open DeepSeek models
Qwen3.5-27B

The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of...

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DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...