GLM-5.3 versus GLM-5.3-Flash

Two models head to head

This comparison pits two open-weight models that you can install on your own servers against each other: GLM-5.3 and GLM-5.3-Flash, both built by Zhipu AI (Z.ai). The first dates from August 14, 2026, the second from September 18, 2026.

All figures below come from public sources checked on October 22, 2026: models.dev and OpenRouter for prices and capabilities, Epoch AI for scores.

Performance

On our capability index, GLM-5.3 scores 78.8 out of 100 and GLM-5.3-Flash 71.9. GLM-5.3 leads by 6.9 points.

On the 5 benchmarks reported for both, GLM-5.3 wins 4 times and GLM-5.3-Flash 1:

• GPQA Diamond (PhD-level science questions): GLM-5.3 90.9%, GLM-5.3-Flash 90.2%
• OTIS Mock AIME (competition mathematics problems): GLM-5.3 91.1%, GLM-5.3-Flash 93.9%
• FrontierMath (very hard research-level mathematics): GLM-5.3 68.8%, GLM-5.3-Flash 55.8%
• FrontierCode (advanced programming tasks): GLM-5.3 40.1%, GLM-5.3-Flash 31.8%
• APEX-Agents (professional tasks carried out by an agent): GLM-5.3 56.6%, GLM-5.3-Flash 52.8%

Which one costs less?

GLM-5.3 costs $1.2 per million input tokens and $4.18 per million output tokens; GLM-5.3-Flash costs $0.30 and $1.05.

For a typical agent task (read 20,000 tokens, write 2,000), expect $0.032 with GLM-5.3 versus $0.008 with GLM-5.3-Flash. GLM-5.3-Flash is 4 times cheaper, a gap that adds up quickly over 1,000 tasks: $24.2 difference.

Run the numbers with your own volumes in the agent cost calculator.

Context and capabilities

Both models have the same context window: 1,000,000 tokens, roughly 1,500 pages.

Reasoning mode: GLM-5.3 yes, GLM-5.3-Flash yes. Tool calling: GLM-5.3 yes, GLM-5.3-Flash yes. Image input: GLM-5.3 no, GLM-5.3-Flash yes.

Both publish their weights: you can host them yourself.

In short

Our reading of the data:

• Choose GLM-5.3 for a higher capability index.
• Choose GLM-5.3-Flash for a lower cost and image input.

This verdict relies on public figures; it does not replace a trial on your own tasks.