DeepSeek-R1-0528 vs GLM-4.5V
Comparing DeepSeek-R1-0528 and GLM-4.5V across benchmarks, pricing, and capabilities.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek-R1-0528 and GLM-4.5V trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-R1-0528 is roughly 1.1x 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 DeepSeek-R1-0528
- cost matters — it's about 1.1x cheaper per token
Choose GLM-4.5V
- you want the most recent training data — it shipped Aug 2025
At a glance
The differences that matter most.
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 0 for GLM-4.5V
DeepSeek-R1-0528 and GLM-4.5Vdon'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, DeepSeek-R1-0528 ($0.50/1M tokens) is 1.1x cheaper than GLM-4.5V ($0.55/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.0x cheaper than GLM-4.5V ($2.19/1M tokens).
In conclusion, GLM-4.5V is more expensive than DeepSeek-R1-0528.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 563.0B more parameters than GLM-4.5V, making it 521.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.5V supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
GLM-4.5V
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
DeepSeek-R1-0528 was released on 2025-05-28, while GLM-4.5V was released on 2025-08-11.
GLM-4.5V is 3 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Aug 11, 2025
1.1 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. GLM-4.5V is available from Fireworks, Novita.
DeepSeek-R1-0528
GLM-4.5V
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and GLM-4.5V side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs GLM-4.5V.