DeepSeek-R1-Distill-Qwen-32B
About DeepSeek-R1-Distill-Qwen-32B
DeepSeek-R1-Distill-Qwen-32B is a distilled model based on Qwen2.5-32B. The model was fine-tuned using 800k curated samples generated by DeepSeek-R1 and demonstrates exceptional performance across mathematics, programming, and reasoning tasks. It achieved impressive results in various benchmarks including AIME 2024, MATH-500, and GPQA Diamond, with a notable 94.3% accuracy on MATH-500, showcasing its strong mathematical reasoning capabilities
Explore how DeepSeek-R1-Distill-Qwen-32B's exceptional reasoning, mathematical, and programming capabilities can solve complex, real-world problems.
Advanced Scientific Problem Solving
Leverage DeepSeek-R1-Distill-Qwen-32B's superior mathematical and reasoning capabilities to tackle complex scientific challenges, from theoretical physics to biochemical modeling.
Use Case Example:
"Aided a quantum computing team by deriving novel algorithms for error correction, significantly accelerating their research timeline."
Multi-Language Code Analysis & Refinement
Go beyond basic debugging. Analyze large codebases across various languages to pinpoint subtle logical flaws, optimize algorithms, and enhance system security.
Use Case Example:
"Identified a critical race condition in a Rust-based blockchain application by tracing concurrent execution paths, providing a precise, secure fix."
Quantitative Financial Strategy
Perform deep quantitative analysis on vast financial datasets, identify intricate market patterns, and formulate robust algorithmic trading or investment strategies.
Use Case Example:
"Developed a high-frequency trading algorithm by analyzing historical market data and economic indicators, outperforming traditional models by 15%."
Intelligent System & Compliance Audits
Automate the auditing of complex systems, from regulatory documents to intricate engineering designs, ensuring compliance and identifying critical vulnerabilities.
Use Case Example:
"Audited a large-scale cloud infrastructure configuration for compliance with GDPR and SOC 2, flagging several misconfigurations and suggesting remediation steps."
Metadata
Specification
State
Deprecated
Architecture
Dense Transformer
Calibrated
No
Mixture of Experts
No
Total Parameters
32B
Activated Parameters
32B
Reasoning
No
Precision
FP8
Context length
131K
Max Tokens
131K
Compare with Other Models
See how this model stacks up against others.
DeepSeek
chat
DeepSeek-V4-Pro
Release on: Apr 24, 2026
Total Context:
1049K
Max output:
393K
Input:
$
1.74
/ M Tokens
Output:
$
3.48
/ M Tokens
DeepSeek
chat
DeepSeek-V4-Flash
Release on: Apr 24, 2026
Total Context:
1049K
Max output:
393K
Input:
$
0.14
/ M Tokens
Output:
$
0.28
/ M Tokens
DeepSeek
chat
DeepSeek-V3.2
Release on: Dec 4, 2025
Total Context:
164K
Max output:
164K
Input:
$
0.27
/ M Tokens
Output:
$
0.42
/ M Tokens
DeepSeek
chat
DeepSeek-V3.2-Exp
Release on: Oct 10, 2025
Total Context:
164K
Max output:
164K
Input:
$
0.27
/ M Tokens
Output:
$
0.41
/ M Tokens
DeepSeek
chat
DeepSeek-V3.1-Terminus
Release on: Sep 29, 2025
Total Context:
164K
Max output:
164K
Input:
$
0.27
/ M Tokens
Output:
$
1.0
/ M Tokens
DeepSeek
chat
DeepSeek-V3.1
Release on: Aug 25, 2025
Total Context:
164K
Max output:
164K
Input:
$
0.27
/ M Tokens
Output:
$
1.0
/ M Tokens
DeepSeek
chat
DeepSeek-V3
Release on: Dec 26, 2024
Total Context:
164K
Max output:
164K
Input:
$
0.25
/ M Tokens
Output:
$
1.0
/ M Tokens
DeepSeek
chat
DeepSeek-R1
Release on: May 28, 2025
Total Context:
164K
Max output:
164K
Input:
$
0.5
/ M Tokens
Output:
$
2.18
/ M Tokens
DeepSeek
chat
DeepSeek-R1-Distill-Qwen-32B
Release on: Jan 20, 2025
Total Context:
131K
Max output:
131K
Input:
$
0.18
/ M Tokens
Output:
$
0.18
/ M Tokens
