GLM-4.5V vs Qwen3.8-Flash-Next
Comparing GLM-4.5V and Qwen3.8-Flash-Next across benchmarks, pricing, and capabilities.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-4.5V and Qwen3.8-Flash-Next trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
Based on current benchmark, pricing, and model metadata for 2026.
Choose GLM-4.5V
- you want predictable pricing at $0.55/M input and $2.19/M output
Choose Qwen3.8-Flash-Next
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-4.5V and Qwen3.8-Flash-Nextdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Model Size
Parameter count comparison
Qwen3.8-Flash-Next has 72.0B more parameters than GLM-4.5V, making it 66.7% larger.
Context Window
Maximum input and output token capacity
Only GLM-4.5V specifies input context (131,072 tokens). Only GLM-4.5V specifies output context (131,072 tokens).
Input Capabilities
Supported data types and modalities
Both GLM-4.5V and Qwen3.8-Flash-Next support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-4.5V
Qwen3.8-Flash-Next
License
Usage and distribution terms
GLM-4.5V is licensed under MIT, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Qwen Community License 1.0
Open weights
Release Timeline
When each model was launched
GLM-4.5V was released on 2025-08-11, while Qwen3.8-Flash-Next was released on 2026-08-26.
Qwen3.8-Flash-Next is 13 months newer than GLM-4.5V.
Aug 11, 2025
1.0 years ago
Aug 26, 2026
0 days ago
1.0yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.5V and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.5V vs Qwen3.8-Flash-Next.