Qwen3-32B

reasoning

Qwen3-32B is the most powerful dense model in the series, featuring 32 billion parameters, a 64-layer architecture, and 64 attention heads, with support for a context window of 128K tokens. This model represents the pinnacle of dense architecture within the Qwen3 lineup, delivering performance comparable to leading proprietary solutions across most tasks. Developers emphasize that thanks to architectural innovations and training on 36 trillion tokens of high-quality data, Qwen3-32B achieves quality on par with Qwen2.5-72B, but with twice as few parameters.

The model demonstrates outstanding results across all benchmarks, particularly excelling in programming, mathematical problem-solving, and knowledge-intensive domains in science and engineering. Qwen3-32B is capable of handling tasks at the level of senior-level experts and delivers quality suitable for mission-critical commercial applications. Full support for all 119 languages at the highest quality makes this model a universal solution for applications requiring international reach.

This model is designed for flagship products from major technology companies, national research initiatives, mission-critical AI systems, and any application where quality is the top priority. Qwen3-32B is ideal for building premium-tier AI assistants, advanced analytical systems, professional-grade development tools, and any use cases demanding the highest level of natural language processing quality.


Announce Date: 29.04.2025
Parameters: 33B
Context: 132K
Layers: 64
Attention Type: Full or Sliding Window Attention
Developer: Qwen
Transformers Version: 4.51.0
License: Apache 2.0

Public endpoint

Use our pre-built public endpoints for free to test inference and explore Qwen3-32B 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 Qwen3-32B

Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-2.16.32.160
20,000.0
tensor
2 $0.54 0.140 Launch
teslaa2-2.16.32.160
20,000.0
tensor
2 $0.57 0.140 Launch
teslaa10-2.16.64.160
20,000.0
tensor
2 $0.93 0.590 Launch
rtx2080ti-4.16.32.160
20,000.0
tensor
4 $1.12 0.321 Launch
teslav100-1.12.64.160
20,000.0
1 $1.20 0.218 Launch
rtxa5000-2.16.64.160.nvlink
20,000.0
tensor
2 $1.23 0.590 Launch
teslaa10-3.16.96.160
131,072.0
pipeline
3 $1.34 1.187 Launch
rtx3090-2.16.64.160
20,000.0
tensor
2 $1.56 49.810 0.590 Launch
rtx5090-1.16.64.160
20,000.0
1 $1.59 0.218 Launch
teslaa10-4.16.64.160
131,072.0
tensor
4 $1.62 1.783 Launch
teslaa2-6.32.128.160
131,072.0
pipeline
6 $1.65 1.627 Launch
rtx3080-4.16.64.160
20,000.0
tensor
4 $1.82 0.208 Launch
rtx4090-2.16.64.160
20,000.0
tensor
2 $1.92 58.920 0.590 Launch
teslav100-2.16.64.240
131,072.0
tensor
2 $2.22 1.040 Launch
rtx3090-3.16.96.160
131,072.0
pipeline
3 $2.29 1.187 Launch
rtxa5000-4.16.128.160.nvlink
131,072.0
tensor
4 $2.34 1.783 Launch
teslaa100-1.16.64.160
131,072.0
1 $2.37 54.180 1.568 Launch
rtx4090-3.16.96.160
131,072.0
pipeline
3 $2.83 1.187 Launch
rtx3090-4.16.64.160
131,072.0
tensor
4 $2.89 1.783 Launch
rtx5090-2.16.64.160
131,072.0
tensor
2 $2.93 74.380 1.040 Launch
rtx4090-4.16.64.160
131,072.0
tensor
4 $3.60 1.783 Launch
h100-1.16.64.160
131,072.0
1 $3.83 60.720 1.568 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 1.962 Launch
h200-1.16.128.160
131,072.0
1 $4.74 3.283 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-4.16.64.160
20,000.0
tensor
4 $0.96 0.414 Launch
teslaa2-4.32.128.160
20,000.0
tensor
4 $1.26 0.414 Launch
teslaa10-3.16.96.160
20,000.0
pipeline
3 $1.34 0.718 Launch
teslaa10-4.12.48.160
20,000.0
tensor
4 $1.57 1.314 Launch
teslaa2-6.32.128.160
131,072.0
pipeline
6 $1.65 1.158 Launch
teslaa10-4.16.128.160
131,072.0
tensor
4 $1.75 1.314 Launch
teslav100-2.16.64.240
20,000.0
tensor
2 $2.22 0.571 Launch
rtx3090-3.16.96.160
20,000.0
pipeline
3 $2.29 0.718 Launch
rtxa5000-4.16.128.160.nvlink
131,072.0
tensor
4 $2.34 1.314 Launch
teslaa100-1.16.64.160
20,000.0
1 $2.37 1.099 Launch
teslaa100-1.16.128.160
131,072.0
1 $2.50 1.099 Launch
rtx4090-3.16.96.160
20,000.0
pipeline
3 $2.83 0.718 Launch
rtx3090-4.16.64.160
20,000.0
tensor
4 $2.89 1.314 Launch
rtx5090-2.16.64.160
20,000.0
tensor
2 $2.93 0.571 Launch
rtx3090-4.16.96.320
131,072.0
tensor
4 $2.97 1.314 Launch
rtx4090-4.16.64.160
20,000.0
tensor
4 $3.60 1.314 Launch
rtx4090-4.16.96.320
131,072.0
tensor
4 $3.68 1.314 Launch
h100-1.16.64.160
20,000.0
1 $3.83 1.099 Launch
teslav100-3.64.256.320
131,072.0
pipeline
3 $3.89 1.393 Launch
h100-1.16.128.160
131,072.0
1 $3.95 1.099 Launch
h100nvl-1.16.96.160
131,072.0
1 $4.11 1.493 Launch
rtx5090-3.16.96.160
131,072.0
pipeline
3 $4.34 1.393 Launch
teslav100-4.32.96.160
131,072.0
tensor
4 $4.35 2.214 Launch
h200-1.16.128.160
131,072.0
1 $4.74 2.814 Launch
rtx5090-4.16.128.160
131,072.0
tensor
4 $5.74 2.214 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-6.32.128.160
20,000.0
pipeline
6 $1.65 0.184 Launch
teslaa10-4.16.128.160
20,000.0
tensor
4 $1.75 0.340 Launch
rtxa5000-4.16.128.160.nvlink
20,000.0
tensor
4 $2.34 0.340 Launch
teslaa100-1.16.128.160
20,000.0
1 $2.50 0.124 Launch
rtx3090-4.16.96.320
20,000.0
tensor
4 $2.97 0.340 Launch
rtxa5000-6.24.192.160.nvlink
131,072.0
pipeline
6 $3.50 1.534 Launch
rtx4090-4.16.96.320
20,000.0
tensor
4 $3.68 0.340 Launch
teslav100-3.64.256.320
20,000.0
pipeline
3 $3.89 0.418 Launch
h100-1.16.128.160
20,000.0
1 $3.95 0.124 Launch
h100nvl-1.16.96.160
20,000.0
1 $4.11 0.518 Launch
rtx5090-3.16.96.160
20,000.0
pipeline
3 $4.34 0.418 Launch
teslav100-4.32.96.160
20,000.0
tensor
4 $4.35 1.240 Launch
rtxa5000-8.24.256.160.nvlink
131,072.0
tensor
8 $4.61 2.728 Launch
teslav100-4.32.256.160
131,072.0
tensor
4 $4.66 1.240 Launch
teslaa100-2.24.128.160.nvlink
131,072.0
tensor
2 $4.67 2.296 Launch
h200-1.16.128.160
131,072.0
1 $4.74 1.840 Launch
rtx5090-4.16.128.160
131,072.0
tensor
4 $5.74 1.240 Launch
rtx4090-6.44.256.160
131,072.0
pipeline
6 $5.83 1.534 Launch
rtx4090-8.44.256.160
131,072.0
tensor
8 $7.51 2.728 Launch
h100-2.24.256.160
131,072.0
tensor
2 $7.84 2.296 Launch
h100nvl-2.24.192.240
131,072.0
tensor
2 $8.17 3.084 Launch

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