Qwen2.5-7B-Instruct

Qwen2.5-7B is a 7-billion-parameter model featuring 28 layers and a 28/4 attention head architecture, delivering substantially expanded capabilities compared to smaller versions. Its key advantage lies in supporting an extended 128K-token context window while maintaining 8K-token generation capacity, enabling it to process lengthy documents and retain complex multi-step tasks in memory.

The model demonstrates significantly enhanced capabilities in mathematical computations, programming, and logical reasoning due to the incorporation of specialized data during pretraining. It also shows substantial progress in understanding structured data formats including tables and JSON.

Qwen2.5-7B represents the optimal choice for most business applications requiring high-quality natural language processing without excessive infrastructure demands. The model excels at workflow automation, long-document analysis, and building intelligent decision-support systems.


Announce Date: 16.09.2024
Parameters: 8B
Context: 33K
Layers: 28
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 Qwen2.5-7B-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 Qwen2.5-7B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-1.16.16.160
32,768.0
1 $0.33 3.261 Launch
rtx2080ti-1.10.16.500
32,768.0
1 $0.38 1.158 Launch
teslaa2-1.16.32.160
32,768.0
1 $0.38 3.282 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 7.435 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 7.993 Launch
rtx3080-2.16.32.160
32,768.0
tensor
2 $0.97 4.282 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 7.972 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 17.835 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 12.088 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 37.270 Launch
h100-1.16.64.160
32,768.0
1 $3.83 37.233 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 44.545 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 77.504 Launch
h200-1.16.128.160
32,768.0
1 $4.74 69.102 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 141.168 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-1.16.16.160
32,768.0
1 $0.33 2.173 Launch
teslaa2-1.16.32.160
32,768.0
1 $0.38 2.194 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 6.347 Launch
rtx2080ti-2.12.64.160
32,768.0
tensor
2 $0.69 4.193 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 6.904 Launch
rtx3080-2.16.32.160
32,768.0
tensor
2 $0.97 3.194 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 6.883 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 16.747 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 11.000 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 36.181 Launch
h100-1.16.64.160
32,768.0
1 $3.83 36.145 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 43.457 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 76.416 Launch
h200-1.16.128.160
32,768.0
1 $4.74 68.013 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 140.080 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-1.16.32.160
32,768.0
1 $0.53 2.294 Launch
teslat4-2.16.32.160
32,768.0
tensor
2 $0.54 4.346 Launch
teslaa2-2.16.32.160
32,768.0
tensor
2 $0.57 4.388 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 2.851 Launch
rtx2080ti-3.12.24.120
32,768.0
pipeline
3 $0.84 3.684 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 2.830 Launch
rtx2080ti-4.16.32.160
32,768.0
tensor
4 $1.12 8.386 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 12.694 Launch
rtx3080-3.16.64.160
32,768.0
pipeline
3 $1.43 2.186 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 6.947 Launch
rtx3080-4.16.64.160
32,768.0
tensor
4 $1.82 6.388 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 32.128 Launch
h100-1.16.64.160
32,768.0
1 $3.83 32.092 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 39.404 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 72.363 Launch
h200-1.16.128.160
32,768.0
1 $4.74 63.960 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 136.027 Launch

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