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 1.012 Launch
teslaa10-4.16.64.160
131,072.0
tensor
4 $1.62 1.601 Launch
teslaa2-6.32.128.160
131,072.0
pipeline
6 $1.65 1.261 Launch
rtx3090-3.16.96.160
131,072.0
pipeline
3 $2.29 1.100 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 1.612 Launch
rtx4090-3.16.96.160
131,072.0
pipeline
3 $2.83 1.097 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 1.723 Launch
rtx5090-2.16.64.160
131,072.0
tensor
2 $2.93 1.030 Launch
rtx3090-4.16.128.160.nvlink
131,072.0
tensor
4 $3.01 1.723 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 1.718 Launch
h100-1.16.64.160
131,072.0
1 $3.83 1.610 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 2.010 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 3.784 Launch
h200-1.16.128.160
131,072.0
1 $4.74 3.353 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 7.266 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-4.16.64.160
131,072.0
tensor
4 $1.62 1.161 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 1.172 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 1.283 Launch
rtx3090-4.16.128.160.nvlink
131,072.0
tensor
4 $3.01 1.283 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 1.278 Launch
h100-1.16.64.160
131,072.0
1 $3.83 1.170 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 1.570 Launch
rtx5090-3.16.96.160
131,072.0
pipeline
3 $4.34 1.312 Launch
teslaa100-2.24.96.160.nvlink
131,072.0
tensor
2 $4.61 3.344 Launch
h200-1.16.128.160
131,072.0
1 $4.74 2.913 Launch
rtx5090-4.16.128.160
131,072.0
tensor
4 $5.74 2.179 Launch
h200-2.24.256.160.nvlink
131,072.0
tensor
2 $9.40 6.826 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
h200-1.16.128.240
131,072.0
1 $4.74 2.005 Launch
teslaa100-2.24.256.240
131,072.0
tensor
2 $4.93 2.436 Launch
teslaa100-2.24.256.320.nvlink
131,072.0
tensor
2 $4.94 2.436 Launch
rtx5090-4.16.128.320
131,072.0
tensor
4 $5.76 1.271 Launch
rtx4090-6.44.256.240
131,072.0
pipeline
6 $5.84 1.405 Launch
dedicated-rtx3090-8.64.128.960-1
131,072.0
tensor
8 $6.04 2.657 Launch
rtx4090-8.44.256.240
131,072.0
tensor
8 $7.52 2.647 Launch
h100-2.24.256.240
131,072.0
tensor
2 $7.85 2.432 Launch
h100nvl-2.24.192.240
131,072.0
tensor
2 $8.17 3.232 Launch
h200-2.24.256.240.nvlink
131,072.0
tensor
2 $9.41 5.918 Launch

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