Enter opens the highlighted result. Esc closes.

GLM 5.3 Prime vs Extract

Updated October 21, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 Prime Replace Extract
GLM 5.3 PrimeZ.ai
Coding
No data
Overall
No data
Output $/M
$8.80
S ExtractScaledown
Coding
No data
Overall
No data
Output $/M
No data
vs 1M vs 1M context window. About the same size.

GLM 5.3 Prime or Extract: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGLM 5.3 PrimeZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BExtractScaledownNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested either model yet, so price and context are the only way to compare them.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GLM 5.3 Prime not benchmarked, Extract not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GLM 5.3 Prime $8.80 against Extract Free per million output tokens.
Context window
Both take 1M tokens.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GLM 5.3 Prime$0.0072Fits in one request
Extract$0.0000Fits in one request

Extract costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Prime$0.166Fits in one request
Extract$0.0020Fits in one request

Extract costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Prime$0.648Fits in one request
Extract$0.0080Fits in one request

Extract costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GLM 5.3 Prime and Extract
SpecificationZ.ai GLM 5.3 PrimeScaleDown Extract
MakerZ.aiScaledown
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 23, 2026October 13, 2026
Context window1M1M
Input $/Mtok$2.80$0.04
Output $/Mtok$8.80Free
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Prime better than Extract for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GLM 5.3 Prime or Extract?

GLM 5.3 Prime costs $2.80 per million input tokens and $8.80 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 5.3 Prime or Extract?

Neither: both take 1M tokens.

Has any benchmark tested both GLM 5.3 Prime and Extract?

No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 21, 2026.

Compare next