Comparisons

Gemini 3.1 Pro vs GLM 5.2

On provider list prices, GLM 5.2 costs $1.40 per million input tokens against $2 for Gemini 3.1 Pro: 1.4x apart. Output is $4.40 against $12 (2.7x). On Allocate both bill at list plus the 7% transaction fee.

Gemini 3.1 ProG GLM 5.2
LabGoogleZai Org
AccessAPI onlyOpen weights
Context window1M tokens256K tokens
List price, input$2 / M tokens$1.4 / M tokens
List price, output$12 / M tokens$4.4 / M tokens
Cached inputn/a$0.26 / M tokens
LicenseProprietary APINot listed
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 $3,220 a month on GLM 5.2 and $6,600 on Gemini 3.1 Pro at list: a gap of $3,380, or 2.0x.

Gemini 3.1 Pro reads 1M tokens per request against 256K for GLM 5.2, 3.8x the window. That decides which one can take whole documents without splitting them.

GLM 5.2$1.40$4.40
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 GLM 5.2 for

  • Agents on open weights
  • Code and structured outputs
  • Fine-tuning toward an owned model
GLM 5.2 details

Common questions

Which is cheaper, Gemini 3.1 Pro or GLM 5.2?

GLM 5.2, on this workload shape. At list prices it is $1.40/$4.40 per million tokens in and out against $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $1.50/$4.71 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 GLM 5.2.

Can I fine-tune Gemini 3.1 Pro or GLM 5.2?

GLM 5.2 publishes open weights (Not listed) 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.