Model Comparison
DeepSeek-R1
vs
GLM-4.5V
Feb 15, 2026
Pricing
Input
$
0.5
/ M Tokens
$
0.14
/ M Tokens
Output
$
2.18
/ M Tokens
$
0.86
/ M Tokens
Metadata
Specification
State
Available
Available
Architecture
MoE
GLM-V family, based on GLM-4.5-Air, incorporates Chain-of-Thought reasoning, RLCS (Reinforcement Learning with Curriculum Sampling), and a Thinking Mode switch, with Mixture of Experts (MoE)
Calibrated
No
Yes
Mixture of Experts
Yes
Yes
Total Parameters
671B
106B
Activated Parameters
37B
12B
Reasoning
No
No
Precision
FP8
FP8
Context length
164K
66K
Max Tokens
164K
66K
Supported Functionality
Serverless
Supported
Supported
Serverless LoRA
Not supported
Not supported
Fine-tuning
Not supported
Not supported
Embeddings
Not supported
Not supported
Rerankers
Not supported
Not supported
Support image input
Not supported
Not supported
JSON Mode
Supported
Not supported
Structured Outputs
Not supported
Not supported
Tools
Supported
Supported
Fim Completion
Supported
Not supported
Chat Prefix Completion
Supported
Not supported
DeepSeek-R1 in Comparison
See how DeepSeek-R1 compares with other popular models across key dimensions.
VS
MiniMax-M2.5
VS
GLM-5
VS
Step-3.5-Flash
VS
GLM-4.7
VS
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VS
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VS
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VS
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VS
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VS
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VS
Qwen3-VL-235B-A22B-Instruct
VS
Qwen3-VL-235B-A22B-Thinking
VS
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VS
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VS
Kimi-K2-Instruct-0905
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