GLM-4.5V vs GLM-4.7-Flash
Comparing GLM-4.5V and GLM-4.7-Flash across benchmarks, pricing, and capabilities.
Zhipu AI · Zhipu AI · Updated for 2026
Which is better?
GLM-4.5V and GLM-4.7-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GLM-4.7-Flash is roughly 6.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-4.5V also accepts a larger context window (131,072 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-4.5V
- you process long inputs — it offers a 131,072 token context window
Choose GLM-4.7-Flash
- cost matters — it's about 6.3x cheaper per token
- you want the most recent training data — it shipped Jan 2026
At a glance
The differences that matter most.
Individual benchmarks
0 reported for GLM-4.5V · 6 for GLM-4.7-Flash
GLM-4.5V and GLM-4.7-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.5V ($0.55/1M tokens) is 7.9x more expensive than GLM-4.7-Flash ($0.07/1M tokens).
For output processing, GLM-4.5V ($2.19/1M tokens) is 5.5x more expensive than GLM-4.7-Flash ($0.40/1M tokens).
In conclusion, GLM-4.5V is more expensive than GLM-4.7-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.5V has 78.0B more parameters than GLM-4.7-Flash, making it 260.0% larger.
Context Window
Maximum input and output token capacity
GLM-4.5V accepts 131,072 input tokens compared to GLM-4.7-Flash's 128,000 tokens. GLM-4.5V can generate longer responses up to 131,072 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.5V supports multimodal inputs, whereas GLM-4.7-Flash does not.
GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-4.5V
GLM-4.7-Flash
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-4.5V was released on 2025-08-11, while GLM-4.7-Flash was released on 2026-01-19.
GLM-4.7-Flash is 5 months newer than GLM-4.5V.
Aug 11, 2025
1.1 years ago
Jan 19, 2026
8 months ago
5mo 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-4.5V is available from Fireworks, Novita. GLM-4.7-Flash is available from ZAI.
GLM-4.5V
GLM-4.7-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.5V and GLM-4.7-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.5V vs GLM-4.7-Flash.