DeepSeek R1 Distill Qwen 32B vs GLM-4.5V
Comparing DeepSeek R1 Distill Qwen 32B and GLM-4.5V across benchmarks, pricing, and capabilities.
DeepSeek · Zhipu AI · Updated for 2026
Which is better?
DeepSeek R1 Distill Qwen 32B and GLM-4.5V trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek R1 Distill Qwen 32B is roughly 7.1x 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 DeepSeek R1 Distill Qwen 32B
- cost matters — it's about 7.1x cheaper per token
Choose GLM-4.5V
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Aug 2025
At a glance
The differences that matter most.
Individual benchmarks
4 reported for DeepSeek R1 Distill Qwen 32B · 0 for GLM-4.5V
DeepSeek R1 Distill Qwen 32B 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 Distill Qwen 32B ($0.12/1M tokens) is 4.6x cheaper than GLM-4.5V ($0.55/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 12.2x cheaper than GLM-4.5V ($2.19/1M tokens).
In conclusion, GLM-4.5V is more expensive than DeepSeek R1 Distill Qwen 32B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.5V has 75.2B more parameters than DeepSeek R1 Distill Qwen 32B, making it 229.3% larger.
Context Window
Maximum input and output token capacity
GLM-4.5V accepts 131,072 input tokens compared to DeepSeek R1 Distill Qwen 32B's 128,000 tokens. GLM-4.5V can generate longer responses up to 131,072 tokens, while DeepSeek R1 Distill Qwen 32B is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GLM-4.5V supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B does not.
GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 32B
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 Distill Qwen 32B was released on 2025-01-20, while GLM-4.5V was released on 2025-08-11.
GLM-4.5V is 7 months newer than DeepSeek R1 Distill Qwen 32B.
Jan 20, 2025
1.6 years ago
Aug 11, 2025
1.1 years ago
6mo 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 Distill Qwen 32B is available from DeepInfra. GLM-4.5V is available from Fireworks, Novita.
DeepSeek R1 Distill Qwen 32B
GLM-4.5V
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 32B and GLM-4.5V side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs GLM-4.5V.