AllocateGPT-5.5 vs Qwen3.7 Max
On provider list prices, Qwen3.7 Max costs $1.25 per million input tokens against $5 for GPT-5.5: 4.0x apart. Output is $3.75 against $30 (8.0x). On Allocate both bill at list plus the 7% transaction fee.
GPT-5.5
Qwen3.7 MaxSpecifications and provider list prices from the Allocate catalog, checked 2026-07-08. Billed price is list plus the 7% transaction fee.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $2,813 a month on Qwen3.7 Max and $16,500 on GPT-5.5 at list: a gap of $13,688, or 5.9x.
Qwen3.7 Max reads 1M tokens per request against 400K for GPT-5.5, 2.5x the window. That decides which one can take whole documents without splitting them.
Choose Qwen3.7 Max for
- The lower list price ($1.25 in / $3.75 out per M tokens)
- The longer context window (1M vs 400K tokens)
Common questions
Which is cheaper, GPT-5.5 or Qwen3.7 Max?
Qwen3.7 Max, on this workload shape. At list prices it is $1.25/$3.75 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $1.34/$4.01 against $5.35/$32.10, list plus 7%.
Which has the bigger context window?
Qwen3.7 Max: 1,000,000 tokens (1M) against 400,000 (400K) for GPT-5.5.
Can I fine-tune GPT-5.5 or Qwen3.7 Max?
No. Both are closed models served over API. If you want a model you can train and own, start from an open-weights base in the catalog.
Related comparisons
Run the numbers on your workload
Or don’t choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.