AllocateGemini 3.1 Pro vs Qwen3.7 Max
On provider list prices, Qwen3.7 Max costs $1.25 per million input tokens against $2 for Gemini 3.1 Pro: 1.6x apart. Output is $3.75 against $12 (3.2x). On Allocate both bill at list plus the 7% transaction fee.
Gemini 3.1 Pro
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 $6,600 on Gemini 3.1 Pro at list: a gap of $3,788, or 2.3x.
Choose Gemini 3.1 Pro for
- Judgment-heavy workflows
- Long-context analysis
- Escalation tier above Flash
Choose Qwen3.7 Max for
- The lower list price ($1.25 in / $3.75 out per M tokens)
- Published cached-input pricing ($0.13 per M tokens)
Common questions
Which is cheaper, Gemini 3.1 Pro 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 $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $1.34/$4.01 against $2.14/$12.84, list plus 7%.
Which has the bigger context window?
They match: both read 1,000,000 tokens (1M) per request.
Can I fine-tune Gemini 3.1 Pro 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.