Comparisons

Gemini 3.1 Pro vs Qwen 3.5

On provider list prices, Qwen 3.5 costs $0.60 per million input tokens against $2 for Gemini 3.1 Pro: 3.3x apart. Output is $3.60 against $12 (3.3x). On Allocate both bill at list plus the 7% transaction fee.

Gemini 3.1 Pro Qwen 3.5
LabGoogleQwen
AccessAPI onlyOpen weights
Context window1M tokens256K tokens
List price, input$2 / M tokens$0.6 / M tokens
List price, output$12 / M tokens$3.6 / M tokens
Cached inputn/a$0.35 / M tokens
LicenseProprietary APIApache 2.0
Fine-tunableNoYes

Specifications 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 $1,980 a month on Qwen 3.5 and $6,600 on Gemini 3.1 Pro at list: a gap of $4,620, or 3.3x.

Gemini 3.1 Pro reads 1M tokens per request against 256K for Qwen 3.5, 3.8x the window. That decides which one can take whole documents without splitting them.

Qwen 3.5$0.60$3.60
Gemini 3.1 Pro$2$12
InputOutput

Choose Gemini 3.1 Pro for

  • Judgment-heavy workflows
  • Long-context analysis
  • Escalation tier above Flash
Gemini 3.1 Pro details

Choose Qwen 3.5 for

  • Multilingual support agents
  • Translation-adjacent workflows
  • Fine-tuning under Apache 2.0
Qwen 3.5 details

Common questions

Which is cheaper, Gemini 3.1 Pro 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 $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $0.64/$3.85 against $2.14/$12.84, list plus 7%.

Which has the bigger context window?

Gemini 3.1 Pro: 1,000,000 tokens (1M) against 262,144 (256K) for Qwen 3.5.

Can I fine-tune Gemini 3.1 Pro or Qwen 3.5?

Qwen 3.5 publishes open weights (Apache 2.0) and can be fine-tuned on your own data. Gemini 3.1 Pro 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.