Comparisons

Gemini 3.1 Pro vs GLM 4.7 FP8

On provider list prices, GLM 4.7 FP8 costs $0.45 per million input tokens against $2 for Gemini 3.1 Pro: 4.4x apart. Output is $2 against $12 (6.0x). On Allocate both bill at list plus the 7% transaction fee.

Gemini 3.1 ProG GLM 4.7 FP8
LabGoogleZai Org
AccessAPI onlyOpen weights
Context window1M tokens198K tokens
List price, input$2 / M tokens$0.45 / M tokens
List price, output$12 / M tokens$2 / M tokens
Cached inputn/an/a
LicenseProprietary APIMIT
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 $1,240 a month on GLM 4.7 FP8 and $6,600 on Gemini 3.1 Pro at list: a gap of $5,360, or 5.3x.

Gemini 3.1 Pro reads 1M tokens per request against 198K for GLM 4.7 FP8, 4.9x the window. That decides which one can take whole documents without splitting them.

GLM 4.7 FP8$0.45$2
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 4.7 FP8 for

  • The lower list price ($0.45 in / $2 out per M tokens)
  • Open weights you can fine-tune and own
  • Fine-tuning under a permissive license (MIT)
GLM 4.7 FP8 details

Common questions

Which is cheaper, Gemini 3.1 Pro or GLM 4.7 FP8?

GLM 4.7 FP8, on this workload shape. At list prices it is $0.45/$2 per million tokens in and out against $2/$12 for Gemini 3.1 Pro. Billed on Allocate: $0.48/$2.14 against $2.14/$12.84, list plus 7%.

Which has the bigger context window?

Gemini 3.1 Pro: 1,000,000 tokens (1M) against 202,752 (198K) for GLM 4.7 FP8.

Can I fine-tune Gemini 3.1 Pro or GLM 4.7 FP8?

GLM 4.7 FP8 publishes open weights (MIT) 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.