GLM 5.2 vs GLM 5.3

On provider list prices, GLM 5.2 costs $1.40 per million input tokens against $1.40 for GLM 5.3: effectively level. Output is $4.40 against $4.40.

G GLM 5.2G GLM 5.3

LabZ.aiZ.ai

AccessOpen weightsOpen weights

Context window1M tokens1M tokens

List price, input$1.4 / M tokens$1.4 / M tokens

List price, output$4.4 / M tokens$4.4 / M tokens

Cached input$0.26 / M tokens$0.26 / M tokens

LicenseNot listedNot listed

Fine-tunableYesYes

Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.

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 $3,220 on GLM 5.3 at list: a gap of $0.

GLM 5.2$1.40$4.40

GLM 5.3$1.40$4.40

InputOutput

Choose GLM 5.2 for

Agents on open weights
Code and structured outputs
Fine-tuning toward an owned model

GLM 5.2 details →

Choose GLM 5.3 for

Training toward a model you own

GLM 5.3 details →

Common questions

Which is cheaper, GLM 5.2 or GLM 5.3?

GLM 5.2, on this workload shape. At list prices it is $1.40/$4.40 per million tokens in and out against $1.40/$4.40 for GLM 5.3. Billed on Allocate: $1.50/$4.71 against $1.50/$4.71.

Which has the bigger context window?

They match: both read 1,048,575 tokens (1M) per request.

Can I fine-tune GLM 5.2 or GLM 5.3?

Both publish open weights (GLM 5.2: Not listed; GLM 5.3: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

Related comparisons

GLM 5.2 vs GLM 5.1 FP4 GLM 5.3 vs GLM 5.1 FP4 GLM 5.2 vs GLM 4.7 FP8 GLM 5.2 vs Kimi K2.6 Fp4 GLM 5.2 vs DeepSeek V4 Pro GLM 5.2 vs Inkling FP4

Run the numbers on your workload

LLM price comparison Agent cost calculator GLM 5.2 GLM 5.3

Or do not 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.

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