Qwen2.5-72B-Instruct

Qwen2.5-72B is the flagship open-weight model of the series, featuring 72 billion parameters, 80 layers, and a 64/8 attention head architecture, representing the pinnacle of Alibaba's open-source language model capabilities. The model supports a 128K-token context window with 8K-token generation, enabling it to analyze multiple documents and produce detailed content with exceptional accuracy.

Trained on an extended dataset of 18 trillion tokens with enhanced filtering and specialized data in mathematics and programming, Qwen2.5-72B delivers outstanding performance across a wide range of tasks. Its most remarkable feature is achieving state-of-the-art results among open-weight models while being significantly smaller than competitors. According to the technical report, the model demonstrates performance competitive with Llama-3-405B-Instruct, despite being five times smaller in size.

Distributed under the special Qwen Research License, Qwen2.5-72B is designed for projects requiring the highest quality natural language processing. The model is ideally suited for: fundamental AI research, development of cutting-edge AI products, training and fine-tuning specialized models, serving as a foundation for multimodal systems and building advanced AI agents


Announce Date: 16.09.2024
Parameters: 73B
Context: 33K
Layers: 80
Attention Type: Full Attention
Developer: Qwen
Transformers Version: 4.43.1
License: qwen

Public endpoint

Use our pre-built public endpoints for free to test inference and explore Qwen2.5-72B-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 Qwen2.5-72B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-3.16.96.160
32,768.0
pipeline
3 $1.34 1.574 Launch
teslaa10-4.16.64.160
32,768.0
tensor
4 $1.62 3.442 Launch
teslaa2-6.32.128.160
32,768.0
pipeline
6 $1.65 2.529 Launch
rtx3090-3.16.96.160
32,768.0
pipeline
3 $2.29 1.867 Launch
rtxa5000-4.16.128.160.nvlink
32,768.0
tensor
4 $2.34 3.442 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 3.203 Launch
rtx4090-3.16.96.160
32,768.0
pipeline
3 $2.83 1.856 Launch
rtx3090-4.16.64.160
32,768.0
tensor
4 $2.89 3.832 Launch
rtx5090-2.16.64.160
32,768.0
tensor
2 $2.93 1.431 Launch
rtx4090-4.16.64.160
32,768.0
tensor
4 $3.60 3.817 Launch
h100-1.16.64.160
32,768.0
1 $3.83 3.197 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 4.476 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 10.244 Launch
h200-1.16.128.160
32,768.0
1 $4.74 8.774 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 21.385 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
dedicated-rtx3090-8.64.128.960-1
32,768.0
tensor
8 8.569 Launch
h100nvl-1.16.96.240
32,768.0
1 $4.12 1.543 Launch
rtx5090-3.16.96.240
32,768.0
pipeline
3 $4.35 1.047 Launch
h200-1.16.128.240
32,768.0
1 $4.74 5.840 Launch
teslaa100-2.24.256.240
32,768.0
tensor
2 $4.93 7.311 Launch
teslaa100-2.24.256.320.nvlink
32,768.0
tensor
2 $4.94 7.311 Launch
rtx5090-4.16.128.320
32,768.0
tensor
4 $5.76 3.766 Launch
rtx4090-6.44.256.240
32,768.0
pipeline
6 $5.84 4.373 Launch
rtx4090-8.44.256.240
32,768.0
tensor
8 $7.52 8.539 Launch
h100-2.24.256.240
32,768.0
tensor
2 $7.85 7.298 Launch
h200-2.24.256.240.nvlink
32,768.0
tensor
2 $9.41 18.452 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa100-3.32.384.240
32,768.0
pipeline
3 $7.36 7.411 Launch
rtx4090-8.44.256.240
32,768.0
tensor
8 $7.52 1.768 Launch
h100nvl-2.24.192.240
32,768.0
tensor
2 $8.17 3.086 Launch
rtx5090-6.44.256.240
32,768.0
pipeline
6 $8.86 1.585 Launch
teslaa100-4.16.256.240
32,768.0
tensor
4 $9.14 14.621 Launch
h200-2.24.256.240
32,768.0
tensor
2 $9.41 11.681 Launch
h200-2.24.256.240.nvlink
32,768.0
tensor
2 $9.41 11.681 Launch
teslaa100-4.32.384.320.nvlink
32,768.0
tensor
4 $9.50 14.621 Launch
rtx5090-8.44.256.240
32,768.0
tensor
8 $11.55 7.531 Launch
h100-3.32.384.240
32,768.0
pipeline
3 $11.73 7.392 Launch
h100-4.16.256.240
32,768.0
tensor
4 $14.96 14.596 Launch

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