GLM-5.3 vs Grok 4.5
GLM-5.3 leads the LLM Stats Score 52.7 to 45.4. GLM-5.3 is 1.6x cheaper per token.
Zhipu AI · xAI · Updated for 2026
Which is better?
GLM-5.3 leads the overall LLM Stats Score 52.7 to 45.4, ranking #9 overall.
In the 4 individual benchmarks reported for both models, GLM-5.3 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.3
- overall performance matters — it scores 52.7 and ranks #9 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 1.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
- you need open weights you can self-host or fine-tune
Choose Grok 4.5
- you want predictable pricing at $2.00/M input and $6.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
17 reported for GLM-5.3 · 15 for Grok 4.5
GLM-5.3 outperforms in 4 benchmarks (DeepSWE 1.1, SWE-Marathon, Terminal-Bench 2.1, Terminal-Bench 4.0), while Grok 4.5 is better at 0 benchmarks.
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-5.3 ($1.20/1M tokens) is 1.7x cheaper than Grok 4.5 ($2.00/1M tokens).
For output processing, GLM-5.3 ($4.00/1M tokens) is 1.5x cheaper than Grok 4.5 ($6.00/1M tokens).
In conclusion, Grok 4.5 is more expensive than GLM-5.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,048,576 input tokens compared to Grok 4.5's 500,000 tokens. Only GLM-5.3 specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Grok 4.5 supports multimodal inputs, whereas GLM-5.3 does not.
Grok 4.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3
Grok 4.5
License
Usage and distribution terms
GLM-5.3 is licensed under GLM-5.3 License, while Grok 4.5 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
GLM-5.3 License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Grok 4.5 was released on 2026-07-16.
GLM-5.3 is 1 month newer than Grok 4.5.
Aug 14, 2026
1 months ago
4w newerJul 16, 2026
2 months ago
Knowledge Cutoff
When training data ends
Grok 4.5 has a documented knowledge cutoff of 2026-02-01, while GLM-5.3's cutoff date is not specified.
We can confirm Grok 4.5's training data extends to 2026-02-01, but cannot make a direct comparison without GLM-5.3's cutoff date.
—
Feb 2026
Provider Availability
GLM-5.3 is available from DeepInfra, FriendliAI, Novita, ZAI. Grok 4.5 is available from xAI.
GLM-5.3
Grok 4.5
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Grok 4.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Grok 4.5.