API cost decision in 10 seconds

Qwen3.5-35B-A3B vs Qwen2.5 VL 72B Instruct

Pick Qwen2.5 VL 72B Instruct for lower cost; pick Qwen3.5-35B-A3B only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen2.5 VL 72B Instruct for lower cost; pick Qwen3.5-35B-A3B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Qwen2.5 VL 72B Instruct is estimated at $0.62 vs $0.64 for Qwen3.5-35B-A3B, saving $0.01 (2.2% lower).

Cost-first pickQwen2.5 VL 72B Instruct
Context-first pickQwen3.5-35B-A3B
Sample savings$0.012.2%
10x traffic gap$0.14

Qwen3.5-35B-A3B has more context, but Qwen2.5 VL 72B Instruct saves $0.01 on the standard workload. At 10x that traffic, the same price gap is about $0.14. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3.5-35B-A3B, balanced workload favors Qwen2.5 VL 72B Instruct, and output-heavy chatbot favors Qwen2.5 VL 72B Instruct.

Workload shapeToken mixBetter pickQwen3.5-35B-A3BQwen2.5 VL 72B Instruct
Input-heavy / RAG5M input + 500K outputQwen3.5-35B-A3B$1.2$1.62
Balanced workload1M input + 1M outputQwen2.5 VL 72B Instruct$1.14$1
Output-heavy chatbot1M input + 5M outputQwen2.5 VL 72B Instruct$5.14$4
Cheaper input Qwen3.5-35B-A3B $0.139 vs $0.25 / 1M

Qwen3.5-35B-A3B is $0.11 cheaper per 1M input tokens (44.4% lower; 1.8x difference).

Cheaper output Qwen2.5 VL 72B Instruct $1 vs $0.75 / 1M

Qwen2.5 VL 72B Instruct is $0.25 cheaper per 1M output tokens (25% lower; 1.33x difference).

Larger context Qwen3.5-35B-A3B 262.14K vs 131.07K

Qwen3.5-35B-A3B has 131.07K more context (2x larger).

Sample workload Qwen2.5 VL 72B Instruct $0.64 vs $0.62

Qwen2.5 VL 72B Instruct is $0.01 cheaper on the standard workload (2.2% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.5-35B-A3B Calculating… Estimated API cost
Qwen2.5 VL 72B Instruct 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

Qwen3.5-35B-A3B has the lower input price; Qwen2.5 VL 72B Instruct has the lower output price; Qwen3.5-35B-A3B offers the larger context window. For the 1M input plus 500K output sample, Qwen2.5 VL 72B Instruct is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.64 for Qwen3.5-35B-A3B and $0.62 for Qwen2.5 VL 72B Instruct.

Best Fit

Choose Qwen3.5-35B-A3B when you care most about lower input-token price, and larger context window.

Choose Qwen2.5 VL 72B Instruct when you care most about lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen2.5 VL 72B Instruct is estimated at $0.62 vs $0.64 for Qwen3.5-35B-A3B, saving $0.01 (2.2% lower).
  • Qwen2.5 VL 72B Instruct is $0.01 cheaper on the standard workload (2.2% lower).
  • Qwen3.5-35B-A3B is $0.11 cheaper per 1M input tokens (44.4% lower; 1.8x difference).
  • Qwen2.5 VL 72B Instruct is $0.25 cheaper per 1M output tokens (25% lower; 1.33x difference).
  • Qwen3.5-35B-A3B has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureQwen3.5-35B-A3B
(Qwen)
Qwen2.5 VL 72B Instruct
(Qwen)
Input Price
prompt tokens per 1M
$0.139$0.25
Completion Price
per 1M tokens
$1$0.75
Sample Workload Cost
1M input + 500K output
$0.64$0.62
Context Window262.14K131.07K
Release Date
Popularity#65#150

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen2.5 VL 72B InstructOn the standard 1M input plus 500K output workload, Qwen2.5 VL 72B Instruct is estimated at $0.62 vs $0.64 for Qwen3.5-35B-A3B, saving $0.01 (2.2% lower).
High-volume input processingQwen3.5-35B-A3BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen2.5 VL 72B InstructLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3.5-35B-A3BA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

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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.

Open provider hubs

Qwen catalog

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

Open Qwen models
Qwen3.5-35B-A3B

The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency. Its overall...

Qwen2.5 VL 72B Instruct

Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.