GLM-4.7 vs GLM-5.1
GLM-4.7 and GLM-5.1 are closely matched at 34.3 and 39.2 on the LLM Stats Score. GLM-4.7 is 2.3x cheaper per token.
Zhipu AI · Zhipu AI · Updated for 2026
Which is better?
GLM-4.7 and GLM-5.1 are closely matched on the overall LLM Stats Score at 34.3 and 39.2.
In the 5 individual benchmarks reported for both models, GLM-5.1 wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-4.7 is roughly 2.3x 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-4.7
- cost matters — it's about 2.3x cheaper per token
Choose GLM-5.1
- your work emphasizes coding and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
- you want the most recent training data — it shipped Apr 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for GLM-4.7 · 18 for GLM-5.1
GLM-4.7 outperforms in 0 benchmarks, while GLM-5.1 is better at 5 benchmarks (BrowseComp, GPQA, Humanity's Last Exam, IMO-AnswerBench, Terminal-Bench 2.0).
GLM-5.1 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-4.7 ($0.40/1M tokens) is 2.6x cheaper than GLM-5.1 ($1.05/1M tokens).
For output processing, GLM-4.7 ($1.75/1M tokens) is 2.0x cheaper than GLM-5.1 ($3.50/1M tokens).
In conclusion, GLM-5.1 is more expensive than GLM-4.7.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.1 has 396.0B more parameters than GLM-4.7, making it 110.6% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 202,752 tokens. Both models can generate responses up to 202,752 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.7 supports multimodal inputs, whereas GLM-5.1 does not.
GLM-4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-4.7
GLM-5.1
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GLM-4.7 was released on 2025-12-22, while GLM-5.1 was released on 2026-04-07.
GLM-5.1 is 4 months newer than GLM-4.7.
Dec 22, 2025
9 months ago
Apr 7, 2026
5 months ago
3mo 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-4.7 is available from DeepInfra, Fireworks, Novita. GLM-5.1 is available from DeepInfra, FriendliAI, ZAI.
GLM-4.7
GLM-5.1
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.7 and GLM-5.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.7 vs GLM-5.1.