GLM-5 vs GLM-4.7-Flash Comparison
Comparing GLM-5 and GLM-4.7-Flash across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while GLM-4.7-Flash is better at 0 benchmarks.
GLM-5 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 14.3x more expensive than GLM-4.7-Flash ($0.07/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 8.0x more expensive than GLM-4.7-Flash ($0.40/1M tokens).
In conclusion, GLM-5 is more expensive than GLM-4.7-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5 has 714.0B more parameters than GLM-4.7-Flash, making it 2380.0% larger.
Context Window
Maximum input and output token capacity
GLM-5 accepts 200,000 input tokens compared to GLM-4.7-Flash's 128,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.
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-5 was released on 2026-02-11, while GLM-4.7-Flash was released on 2026-01-19.
GLM-5 is 1 month newer than GLM-4.7-Flash.
Feb 11, 2026
1 months ago
3w newerJan 19, 2026
1 months ago
Knowledge 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 is available from ZAI. GLM-4.7-Flash is available from ZAI. The availability of providers can affect quality of the model and reliability.
GLM-5
GLM-4.7-Flash
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
GLM-4.7-Flash
View detailsZhipu AI
Detailed Comparison
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