AllocateGPT-5.5 vs Qwen 3.5
On provider list prices, Qwen 3.5 costs $0.60 per million input tokens against $5 for GPT-5.5: 8.3x apart. Output is $3.60 against $30 (8.3x).
GPT-5.5
Qwen 3.5Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.
What the numbers say
Take 1,000,000 requests a month at 1,200 input and 350 output tokens each. That workload costs $1,980 a month on Qwen 3.5 and $16,500 on GPT-5.5 at list: a gap of $14,520, or 8.3x.
GPT-5.5 reads 400K tokens per request against 256K for Qwen 3.5, 1.5x the window. That decides which one can take whole documents without splitting them.
Choose Qwen 3.5 for
- Multilingual support agents
- Translation-adjacent workflows
- Fine-tuning under Apache 2.0
Common questions
Which is cheaper, GPT-5.5 or Qwen 3.5?
Qwen 3.5, on this workload shape. At list prices it is $0.60/$3.60 per million tokens in and out against $5/$30 for GPT-5.5. Billed on Allocate: $0.64/$3.85 against $5.35/$32.10.
Which has the bigger context window?
GPT-5.5: 400,000 tokens (400K) against 262,144 (256K) for Qwen 3.5.
Can I fine-tune GPT-5.5 or Qwen 3.5?
Qwen 3.5 publishes open weights (Apache 2.0) and can be fine-tuned on your own data. GPT-5.5 is a closed model served over API; its weights are not available.
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.