Qwen2.5-32B-Instruct

Qwen2.5-32B features 32 billion parameters, 64 layers, and a 40/8 attention head architecture, representing a significant leap in computational power and model capabilities. With support for a 128K-token context window and 8K-token generation capacity, the model can handle exceptionally complex and large-scale tasks.

Qwen2.5-32B reintroduces the 32B parameter size to the Qwen series after its absence in Qwen2, offering users a powerful alternative to the flagship 72B model with lower resource requirements. Trained on 18 trillion high-quality tokens, the model demonstrates robust performance with large datasets, expert-level knowledge in specialized domains, superior abstract reasoning capabilities, and the ability to solve problems requiring deep contextual understanding and multi-step analysis.

Qwen2.5-32B is designed for organizations and research teams that need frontier-model capabilities without the full cost of the largest models. Ideal applications include scientific research, complex software development, high-quality content creation, expert support systems in medicine and law, and as a foundation for building highly specialized AI systems.


Announce Date: 17.09.2024
Parameters: 32B
Context: 33K
Layers: 64
Attention Type: Full Attention
Developer: Qwen
Transformers Version: 4.43.1
License: Apache 2.0

Public endpoint

Use our pre-built public endpoints for free to test inference and explore Qwen2.5-32B-Instruct 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 Qwen2.5-32B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-3.32.64.160
32,768.0
pipeline
3 $0.88 1.779 Launch
teslaa10-2.16.64.160
32,768.0
tensor
2 $0.93 2.313 Launch
teslat4-4.16.64.160
32,768.0
tensor
4 $0.96 3.211 Launch
teslaa2-3.32.128.160
32,768.0
pipeline
3 $1.06 1.793 Launch
rtx2080ti-4.16.32.160
32,768.0
tensor
4 $1.12 1.371 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 2.313 Launch
teslaa2-4.32.128.160
32,768.0
tensor
4 $1.26 3.229 Launch
rtx3090-2.16.64.160
32,768.0
tensor
2 $1.56 2.557 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 1.056 Launch
rtx4090-2.16.64.160
32,768.0
tensor
2 $1.92 2.548 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 6.564 Launch
h100-1.16.64.160
32,768.0
1 $3.83 6.556 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 8.156 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 15.366 Launch
h200-1.16.128.160
32,768.0
1 $4.74 13.528 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 29.292 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-4.16.64.160
32,768.0
tensor
4 $0.96 1.722 Launch
teslaa2-4.32.128.160
32,768.0
tensor
4 $1.26 1.741 Launch
teslaa10-3.16.96.160
32,768.0
pipeline
3 $1.34 2.983 Launch
rtx3090-2.16.64.160
32,768.0
tensor
2 $1.56 1.069 Launch
teslaa10-4.12.48.160
32,768.0
tensor
4 $1.57 5.375 Launch
rtx4090-2.16.64.160
32,768.0
tensor
2 $1.92 1.059 Launch
rtxa5000-4.16.128.160.nvlink
32,768.0
tensor
4 $2.34 5.375 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 5.076 Launch
rtx5090-2.16.64.160
32,768.0
tensor
2 $2.93 2.860 Launch
h100-1.16.64.160
32,768.0
1 $3.83 5.068 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 6.668 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 13.877 Launch
h200-1.16.128.160
32,768.0
1 $4.74 12.039 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 27.804 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-4.16.128.240
32,768.0
tensor
4 $1.76 1.472 Launch
teslaa100-1.16.128.240
32,768.0
1 $2.51 1.173 Launch
rtx3090-4.16.96.320
32,768.0
tensor
4 $2.97 1.959 Launch
rtx4090-4.16.96.320
32,768.0
tensor
4 $3.68 1.941 Launch
h100-1.16.128.240
32,768.0
1 $3.96 1.165 Launch
h100nvl-1.16.96.240
32,768.0
1 $4.12 2.764 Launch
rtx5090-3.16.96.240
32,768.0
pipeline
3 $4.35 2.011 Launch
h200-1.16.128.240
32,768.0
1 $4.74 8.136 Launch
teslaa100-2.24.256.320.nvlink
32,768.0
tensor
2 $4.94 9.974 Launch
rtx5090-4.16.128.320
32,768.0
tensor
4 $5.76 5.543 Launch
h200-2.24.256.240.nvlink
32,768.0
tensor
2 $9.41 23.901 Launch

Related models

Need help?

Contact our dedicated neural networks support team at nn@immers.cloud or send your request to the sales department at sale@immers.cloud.