Qwen2.5-1.5B-Instruct

Qwen2.5-1.5B features 1.5 billion parameters, delivering significantly improved performance over the 0.5B version while maintaining relatively low computational requirements. It retains the same 32K-token context window and 8K-token generation capability, enabling support for a wide range of tasks. This preserves the key advantage of lightweight models—the balance between performance and efficiency. The model demonstrates strong capabilities in logical reasoning, contextual understanding, and coherent text generation across multiple languages (including Russian), while remaining lightweight enough for deployment on computationally constrained, power-sensitive devices.

Qwen2.5-1.5B stands out for its fast response times, versatility, and ability to operate in resource-limited environments while maintaining high-quality responses and instruction comprehension. The model is particularly well-suited for enterprise chatbots, smart assistants, on-premise support systems, as well as educational and research projects where data privacy and autonomous operation are critical.


Announce Date: 17.09.2024
Parameters: 2B
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 Qwen2.5-1.5B-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 Qwen2.5-1.5B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-1.16.16.160
32,768.0
1 $0.33 11.228 Launch
rtx2080ti-1.10.16.500
32,768.0
1 $0.38 7.022 Launch
teslaa2-1.16.32.160
32,768.0
1 $0.38 11.270 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 19.576 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 6.023 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 20.691 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 20.649 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 40.376 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 28.881 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 79.245 Launch
h100-1.16.64.160
32,768.0
1 $3.83 79.171 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 93.796 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 159.713 Launch
h200-1.16.128.160
32,768.0
1 $4.74 142.909 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 287.041 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-1.16.16.160
32,768.0
1 $0.33 10.525 Launch
rtx2080ti-1.10.16.500
32,768.0
1 $0.38 6.319 Launch
teslaa2-1.16.32.160
32,768.0
1 $0.38 10.567 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 18.873 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 5.320 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 19.988 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 19.946 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 39.673 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 28.179 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 78.542 Launch
h100-1.16.64.160
32,768.0
1 $3.83 78.468 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 93.094 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 159.011 Launch
h200-1.16.128.160
32,768.0
1 $4.74 142.206 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 286.339 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-1.16.16.160
32,768.0
1 $0.33 9.165 Launch
rtx2080ti-1.10.16.500
32,768.0
1 $0.38 4.960 Launch
teslaa2-1.16.32.160
32,768.0
1 $0.38 9.208 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 17.514 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 3.961 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 18.628 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 18.586 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 38.314 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 26.819 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 77.182 Launch
h100-1.16.64.160
32,768.0
1 $3.83 77.109 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 91.734 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 157.651 Launch
h200-1.16.128.160
32,768.0
1 $4.74 140.846 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 284.979 Launch

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