API cost decision in 10 seconds

NewQwen3.7 Max vs GPT Audio

Pick Qwen3.7 Max when budget and context both matter.

Pricing data updated: 2026-05-26T11:08:00Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3.7 Max when budget and context both matter.

On the standard 1M input plus 500K output workload, Qwen3.7 Max is estimated at $6.25 vs $7.5 for GPT Audio, saving $1.25 (16.7% lower).

Cost-first pickQwen3.7 Max

Context-first pickQwen3.7 Max

Sample savings$1.2516.7%

10x traffic gap$12.5

Qwen3.7 Max is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $12.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3.7 Max stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Qwen3.7 Max	GPT Audio
Input-heavy / RAG	5M input + 500K output	Qwen3.7 Max	$16.25	$17.5
Balanced workload	1M input + 1M output	Qwen3.7 Max	$10	$12.5
Output-heavy chatbot	1M input + 5M output	Qwen3.7 Max	$40	$52.5

Cheaper input Tie $2.5 vs $2.5 / 1M

Both models report the same input price at $2.5 per 1M tokens.

Cheaper output Qwen3.7 Max $7.5 vs $10 / 1M

Qwen3.7 Max is $2.5 cheaper per 1M output tokens (25% lower; 1.33x difference).

Larger context Qwen3.7 Max 1M vs 128K

Qwen3.7 Max has 872K more context (7.81x larger).

Sample workload Qwen3.7 Max $6.25 vs $7.5

Qwen3.7 Max is $1.25 cheaper on the standard workload (16.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3.7 Max 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

both models tie on input price; Qwen3.7 Max has the lower output price; Qwen3.7 Max offers the larger context window. For the 1M input plus 500K output sample, Qwen3.7 Max is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $6.25 for Qwen3.7 Max and $7.5 for GPT Audio.

Best Fit

Choose Qwen3.7 Max when you care most about 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, Qwen3.7 Max is estimated at $6.25 vs $7.5 for GPT Audio, saving $1.25 (16.7% lower).
Qwen3.7 Max is $1.25 cheaper on the standard workload (16.7% lower).
Both models report the same input price at $2.5 per 1M tokens.
Qwen3.7 Max is $2.5 cheaper per 1M output tokens (25% lower; 1.33x difference).
Qwen3.7 Max has 872K more context (7.81x larger).

Head-to-Head Specs

Feature	NewQwen3.7 Max (Qwen)	GPT Audio (OpenAI)
Input Price prompt tokens per 1M	$2.5	$2.5
Completion Price per 1M tokens	$7.5	$10
Sample Workload Cost 1M input + 500K output	$6.25	$7.5
Context Window	1M	128K
Release Date	2026-05-21	2026-01-19

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3.7 Max	On the standard 1M input plus 500K output workload, Qwen3.7 Max is estimated at $6.25 vs $7.5 for GPT Audio, saving $1.25 (16.7% lower).
High-volume input processing	Tie	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Qwen3.7 Max	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3.7 Max	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Qwen3 Next 80B A3B Instruct (free) can replace Qwen3.7 Max when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3.7 Max when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3.7 Max when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3.7 Max when lower sample workload cost matters most: $0.11.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Grok 4.20 Multi-Agent offers 2M context with $5 sample workload cost.
Grok 4.20 offers 2M context with $2.5 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.

Popular competitors

No popular competitor is currently available.

Cheaper alternatives

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

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Larger context alternatives

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

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Provider catalogs

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Qwen catalog

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

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OpenAI catalog

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

Open OpenAI models

Qwen3.7 Max

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...

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...