GLM-5.3-Flash vs Grok 4.7
GLM-5.3-Flash and Grok 4.7 are closely matched at 48.8 and 46.7 on the LLM Stats Score. GLM-5.3-Flash is 12.6x cheaper per token.
Zhipu AI · xAI · Updated for 2026
Which is better?
GLM-5.3-Flash and Grok 4.7 are closely matched on the overall LLM Stats Score at 48.8 and 46.7.
In the 1 individual benchmarks reported for both models, Grok 4.7 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3-Flash is roughly 12.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash 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-Flash
- cost matters — it's about 12.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose Grok 4.7
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
15 reported for GLM-5.3-Flash · 23 for Grok 4.7
GLM-5.3-Flash outperforms in 0 benchmarks, while Grok 4.7 is better at 1 benchmark (DeepSWE 1.1).
Grok 4.7 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-Flash ($0.15/1M tokens) is 13.3x cheaper than Grok 4.7 ($2.00/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 12.0x cheaper than Grok 4.7 ($6.00/1M tokens).
In conclusion, Grok 4.7 is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Grok 4.7's 500,000 tokens. Only GLM-5.3-Flash specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and Grok 4.7 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Grok 4.7
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Grok 4.7 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Grok 4.7 was released on 2026-09-21.
Grok 4.7 is 1 month newer than GLM-5.3-Flash.
Aug 26, 2026
1 months ago
Sep 21, 2026
1 months ago
3w newerKnowledge Cutoff
When training data ends
Grok 4.7 has a documented knowledge cutoff of 2026-06-01, while GLM-5.3-Flash's cutoff date is not specified.
We can confirm Grok 4.7's training data extends to 2026-06-01, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.
—
Jun 2026
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. Grok 4.7 is available from xAI.
GLM-5.3-Flash
Grok 4.7
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Grok 4.7 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Grok 4.7.