GLM-5.2 vs GLM-5.3
GLM-5.3 leads the LLM Stats Score 54.2 to 46.5. GLM-5.2 is 1.5x cheaper per token.
Zhipu AI · Zhipu AI · Updated for 2026
Which is better?
GLM-5.3 leads the overall LLM Stats Score 54.2 to 46.5, ranking #6 overall.
In the 9 individual benchmarks reported for both models, GLM-5.3 wins 8; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.2 is roughly 1.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.2
- cost matters — it's about 1.5x cheaper per token
- you need open weights you can self-host or fine-tune
Choose GLM-5.3
- overall performance matters — it scores 54.2 and ranks #6 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 8 of 9 exact shared results
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for GLM-5.2 · 16 for GLM-5.3
GLM-5.2 outperforms in 1 benchmarks (Program Bench), while GLM-5.3 is better at 8 benchmarks (DeepSWE 1.1, FrontierSWE, Humanity's Last Exam, NL2Repo, PostTrainBench, SWE-Marathon, Terminal-Bench 2.1, Toolathlon).
GLM-5.3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.95/1M tokens) is 1.5x cheaper than GLM-5.3 ($1.40/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 1.5x cheaper than GLM-5.3 ($4.40/1M tokens).
In conclusion, GLM-5.3 is more expensive than GLM-5.2.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 0.0B more parameters than GLM-5.2, making it 0.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Both models can generate responses up to 131,072 tokens.
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while GLM-5.3 was released on 2026-08-14.
GLM-5.3 is 2 months newer than GLM-5.2.
Jun 16, 2026
2 months ago
Aug 14, 2026
2 weeks ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. GLM-5.3 is available from Novita, ZAI.
GLM-5.2
GLM-5.3
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and GLM-5.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs GLM-5.3.