API cost decision in 10 seconds

🔥DeepSeek V3.2 vs 🔥Qwen3.6 Plus

Pick DeepSeek V3.2 for lower cost; pick Qwen3.6 Plus 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 Qwen3.6 Plus 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 $1.3 for Qwen3.6 Plus, saving $0.86 (66.1% lower).

Cost-first pickDeepSeek V3.2
Context-first pickQwen3.6 Plus
Sample savings$0.8666.1%
10x traffic gap$8.59

Qwen3.6 Plus has more context, but DeepSeek V3.2 saves $0.86 on the standard workload. At 10x that traffic, the same price gap is about $8.59. Use the calculator below to replace the sample workload with your own token volume.

Cheaper input DeepSeek V3.2 $0.252 vs $0.325 / 1M

DeepSeek V3.2 is $0.07 cheaper per 1M input tokens (22.5% lower; 1.29x difference).

Cheaper output DeepSeek V3.2 $0.378 vs $1.95 / 1M

DeepSeek V3.2 is $1.57 cheaper per 1M output tokens (80.6% lower; 5.16x difference).

Larger context Qwen3.6 Plus 131.07K vs 1M

Qwen3.6 Plus has 868.93K more context (7.63x larger).

Sample workload DeepSeek V3.2 $0.44 vs $1.3

DeepSeek V3.2 is $0.86 cheaper on the standard workload (66.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
DeepSeek V3.2 Calculating… Estimated API cost
Qwen3.6 Plus 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

DeepSeek V3.2 has the lower input price; DeepSeek V3.2 has the lower output price; Qwen3.6 Plus 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 $0.44 for DeepSeek V3.2 and $1.3 for Qwen3.6 Plus.

Best Fit

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

Choose Qwen3.6 Plus when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, DeepSeek V3.2 is estimated at $0.44 vs $1.3 for Qwen3.6 Plus, saving $0.86 (66.1% lower).
  • DeepSeek V3.2 is $0.86 cheaper on the standard workload (66.1% lower).
  • DeepSeek V3.2 is $0.07 cheaper per 1M input tokens (22.5% lower; 1.29x difference).
  • DeepSeek V3.2 is $1.57 cheaper per 1M output tokens (80.6% lower; 5.16x difference).
  • Qwen3.6 Plus has 868.93K more context (7.63x larger).
Head-to-Head Specs
Feature🔥DeepSeek V3.2
(DeepSeek)
🔥Qwen3.6 Plus
(Qwen)
Input Price
prompt tokens per 1M
$0.252$0.325
Completion Price
per 1M tokens
$0.378$1.95
Sample Workload Cost
1M input + 500K output
$0.44$1.3
Context Window131.07K1M
Release Date2025-12-012026-04-02
Popularity Rank
current rank
#7#10

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 $1.3 for Qwen3.6 Plus, saving $0.86 (66.1% lower).
High-volume input processingDeepSeek V3.2Lower 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 workQwen3.6 PlusA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Cheaper alternatives

Review low-cost models ranked by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

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

Open provider hubs

DeepSeek catalog

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

Open DeepSeek models

Qwen catalog

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

Open Qwen models
DeepSeek V3.2

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...

Qwen3.6 Plus

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...