API cost decision in 10 seconds

Qwen3.5 397B A17B vs GPT Audio

Pick Qwen3.5 397B A17B when budget and context both matter.

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

Budget verdict

Pick Qwen3.5 397B A17B when budget and context both matter.

On the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $7.5 for GPT Audio, saving $5.94 (79.2% lower).

Cost-first pickQwen3.5 397B A17B
Context-first pickQwen3.5 397B A17B
Sample savings$5.9479.2%
10x traffic gap$59.4

Qwen3.5 397B A17B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $59.4. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3.5 397B A17B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickQwen3.5 397B A17BGPT Audio
Input-heavy / RAG5M input + 500K outputQwen3.5 397B A17B$3.12$17.5
Balanced workload1M input + 1M outputQwen3.5 397B A17B$2.73$12.5
Output-heavy chatbot1M input + 5M outputQwen3.5 397B A17B$12.09$52.5
Cheaper input Qwen3.5 397B A17B $0.39 vs $2.5 / 1M

Qwen3.5 397B A17B is $2.11 cheaper per 1M input tokens (84.4% lower; 6.41x difference).

Cheaper output Qwen3.5 397B A17B $2.34 vs $10 / 1M

Qwen3.5 397B A17B is $7.66 cheaper per 1M output tokens (76.6% lower; 4.27x difference).

Larger context Qwen3.5 397B A17B 262.14K vs 128K

Qwen3.5 397B A17B has 134.14K more context (2.05x larger).

Sample workload Qwen3.5 397B A17B $1.56 vs $7.5

Qwen3.5 397B A17B is $5.94 cheaper on the standard workload (79.2% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.5 397B A17B Calculating… Estimated API cost
GPT Audio 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 397B A17B has the lower input price; Qwen3.5 397B A17B has the lower output price; Qwen3.5 397B A17B offers the larger context window. For the 1M input plus 500K output sample, Qwen3.5 397B A17B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.56 for Qwen3.5 397B A17B and $7.5 for GPT Audio.

Best Fit

Choose Qwen3.5 397B A17B when you care most about lower input-token price, lower output-token price, and larger context window.

Choose GPT Audio when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $7.5 for GPT Audio, saving $5.94 (79.2% lower).
  • Qwen3.5 397B A17B is $5.94 cheaper on the standard workload (79.2% lower).
  • Qwen3.5 397B A17B is $2.11 cheaper per 1M input tokens (84.4% lower; 6.41x difference).
  • Qwen3.5 397B A17B is $7.66 cheaper per 1M output tokens (76.6% lower; 4.27x difference).
  • Qwen3.5 397B A17B has 134.14K more context (2.05x larger).
Head-to-Head Specs
FeatureQwen3.5 397B A17B
(Qwen)
GPT Audio
(OpenAI)
Input Price
prompt tokens per 1M
$0.39$2.5
Completion Price
per 1M tokens
$2.34$10
Sample Workload Cost
1M input + 500K output
$1.56$7.5
Context Window262.14K128K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3.5 397B A17BOn the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $7.5 for GPT Audio, saving $5.94 (79.2% lower).
High-volume input processingQwen3.5 397B A17BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen3.5 397B A17BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3.5 397B A17BA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Qwen catalog

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OpenAI catalog

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The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

GPT Audio

The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...