DeepSeek-R1-Distill-Qwen-32B

DeepSeek-R1-Distill-32B is a distilled model built upon Qwen2.5-32B, incorporating the best reasoning algorithms from DeepSeek-R1 and expert knowledge. It sets new records among open-source dense models across several reasoning benchmarks: AIME 2024–72.6%, MATH-500–94.3%, and others. In practice, this model is nearly on par with the distilled 70-billion-parameter version and even surpasses it in certain tests.

Technically, the model is designed for solving expert-level tasks: complex mathematical computations, code generation and analysis, scientific research, and processing long or intricate contexts. DeepSeek-R1-Distill-32B can be integrated into enterprise systems, cloud services, and platforms for automating intellectual labor. For end-user applications, it is indispensable for building expert systems, scientific assistants, platforms for automating complex business processes, and educational solutions that require thorough and well-articulated explanations in responses.

DeepSeek-R1-Distill-32B is the choice for those seeking maximum performance among open-source models without the need to move to the heaviest systems.


Announce Date: 20.01.2025
Parameters: 33B
Context: 132K
Layers: 64
Attention Type: Full or Sliding Window Attention
Developer: DeepSeek
Transformers Version: 4.43.1
License: Apache 2.0

Public endpoint

Use our pre-built public endpoints for free to test inference and explore DeepSeek-R1-Distill-Qwen-32B capabilities. You can obtain an API access token on the token management page after registration and verification.
Model Name Context Type GPU Status Link
There are no public endpoints for this model yet.

Private server

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

  • maximize endpoint performance,
  • enable full context for long sequences,
  • ensure top-tier security for data processing in an isolated, dedicated environment,
  • use custom weights, such as fine-tuned models or LoRA adapters.

Recommended server configurations for hosting DeepSeek-R1-Distill-Qwen-32B

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-3.16.96.160
131,072.0
pipeline
3 $1.34 1.055 Launch
teslaa10-4.16.64.160
131,072.0
tensor
4 $1.62 1.616 Launch
teslaa2-6.32.128.160
131,072.0
pipeline
6 $1.65 1.323 Launch
rtx3090-3.16.96.160
131,072.0
pipeline
3 $2.29 1.146 Launch
rtxa5000-4.16.128.160.nvlink
131,072.0
tensor
4 $2.34 1.616 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 1.616 Launch
rtx4090-3.16.96.160
131,072.0
pipeline
3 $2.83 1.143 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 1.738 Launch
rtx5090-2.16.64.160
131,072.0
tensor
2 $2.93 1.037 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 1.733 Launch
h100-1.16.64.160
131,072.0
1 $3.83 1.614 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 2.014 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 3.791 Launch
h200-1.16.128.160
131,072.0
1 $4.74 3.357 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 7.273 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-4.16.64.160
131,072.0
tensor
4 $1.62 1.176 Launch
rtxa5000-4.16.128.160.nvlink
131,072.0
tensor
4 $2.34 1.176 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 1.176 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 1.298 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 1.293 Launch
h100-1.16.64.160
131,072.0
1 $3.83 1.174 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 1.574 Launch
rtx5090-3.16.96.160
131,072.0
pipeline
3 $4.34 1.364 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 3.351 Launch
h200-1.16.128.160
131,072.0
1 $4.74 2.917 Launch
rtx5090-4.16.128.160
131,072.0
tensor
4 $5.74 2.194 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 6.833 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
h200-1.16.128.240
131,072.0
1 $4.74 2.009 Launch
teslaa100-2.24.256.240
131,072.0
tensor
2 $4.93 2.444 Launch
teslaa100-2.24.256.320.nvlink
131,072.0
tensor
2 $4.94 2.444 Launch
rtx5090-4.16.128.320
131,072.0
tensor
4 $5.76 1.286 Launch
rtx4090-6.44.256.240
131,072.0
pipeline
6 $5.84 1.472 Launch
dedicated-rtx3090-8.64.128.960-1
131,072.0
tensor
8 $6.04 2.687 Launch
rtx4090-8.44.256.240
131,072.0
tensor
8 $7.52 2.677 Launch
h100-2.24.256.240
131,072.0
tensor
2 $7.85 2.439 Launch
h100nvl-2.24.192.240
131,072.0
tensor
2 $8.17 3.239 Launch
h200-2.24.256.240.nvlink
131,072.0
tensor
2 $9.41 5.925 Launch

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