GLM-5.1 vs Grok 4.7
Grok 4.7 leads the LLM Stats Score 48.5 to 39.2. GLM-5.1 is 1.8x cheaper per token.
Zhipu AI · xAI · Updated for 2026
Which is better?
Grok 4.7 leads the overall LLM Stats Score 48.5 to 39.2, ranking #23 overall.
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-5.1 is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Grok 4.7 also accepts a larger context window (500,000 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-5.1
- cost matters — it's about 1.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Grok 4.7
- overall performance matters — it scores 48.5 and ranks #23 on LLM Stats
- your work emphasizes coding and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 500,000 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
18 reported for GLM-5.1 · 23 for Grok 4.7
GLM-5.1 outperforms in 0 benchmarks, while Grok 4.7 is better at 1 benchmark (CyberGym).
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-5.1 ($1.05/1M tokens) is 1.9x cheaper than Grok 4.7 ($2.00/1M tokens).
For output processing, GLM-5.1 ($3.50/1M tokens) is 1.7x cheaper than Grok 4.7 ($6.00/1M tokens).
In conclusion, Grok 4.7 is more expensive than GLM-5.1.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Grok 4.7 accepts 500,000 input tokens compared to GLM-5.1's 202,752 tokens. Only GLM-5.1 specifies output context (202,752 tokens).
Input capabilities
Documented input modalities across available providers
Grok 4.7 supports multimodal inputs, whereas GLM-5.1 does not.
Grok 4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.1
Grok 4.7
License
Usage and distribution terms
GLM-5.1 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-5.1 was released on 2026-04-07, while Grok 4.7 was released on 2026-09-21.
Grok 4.7 is 6 months newer than GLM-5.1.
Apr 7, 2026
5 months ago
Sep 21, 2026
1 days ago
5mo newerKnowledge Cutoff
When training data ends
Grok 4.7 has a documented knowledge cutoff of 2026-06-01, while GLM-5.1'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-5.1's cutoff date.
—
Jun 2026
Provider Availability
GLM-5.1 is available from DeepInfra, FriendliAI, ZAI. Grok 4.7 is available from xAI.
GLM-5.1
Grok 4.7
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.1 and Grok 4.7 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.1 vs Grok 4.7.