Qwen2.5-14B-Instruct

Qwen2.5-14B features 14 billion parameters, 48 layers, and a 40/8 attention head architecture, representing a substantial increase in computational power and complexity compared to the 7B version. The model supports a 128K-token context window with 8K-token generation capability, enabling it to process voluminous documents and execute complex multi-step tasks.

The uniqueness of Qwen2.5-14B lies in its reintroduction to the series after being absent from Qwen2, effectively bridging the critical gap between 7B and larger models. This size proves particularly valuable for organizations requiring high performance without the substantial costs associated with 32B or 72B-level models. The model demonstrates significant improvements in expert-level knowledge, complex reasoning, and multi-domain task handling capabilities.

Qwen2.5-14B is ideally suited for medium-to-large scale enterprise applications demanding high-quality processing with reasonable infrastructure costs. The model excels in knowledge management systems, comprehensive analytics, and serves as an excellent foundation for developing industry-specific AI solutions.


Announce Date: 16.09.2024
Parameters: 14B
Context: 33K
Layers: 48
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 Qwen2.5-14B-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 Qwen2.5-14B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-1.16.32.160
32,768.0
1 $0.53 1.351 Launch
teslat4-2.16.32.160
32,768.0
tensor
2 $0.54 1.816 Launch
teslaa2-2.16.32.160
32,768.0
tensor
2 $0.57 1.828 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 1.513 Launch
rtx2080ti-3.12.24.120
32,768.0
pipeline
3 $0.84 1.658 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 1.507 Launch
rtx2080ti-4.16.32.160
32,768.0
tensor
4 $1.12 2.728 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 4.251 Launch
rtx3080-3.16.64.160
32,768.0
pipeline
3 $1.43 1.221 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 2.708 Launch
rtx3080-4.16.64.160
32,768.0
tensor
4 $1.82 2.145 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 10.053 Launch
h100-1.16.64.160
32,768.0
1 $3.83 10.042 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 12.175 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 21.654 Launch
h200-1.16.128.160
32,768.0
1 $4.74 19.337 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 40.223 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslat4-3.32.64.160
32,768.0
pipeline
3 $0.88 2.464 Launch
teslaa10-2.16.64.160
32,768.0
tensor
2 $0.93 3.216 Launch
teslat4-4.16.64.160
32,768.0
tensor
4 $0.96 4.146 Launch
teslaa2-3.32.128.160
32,768.0
pipeline
3 $1.06 2.482 Launch
rtx2080ti-4.16.32.160
32,768.0
tensor
4 $1.12 1.693 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 3.216 Launch
teslaa2-4.32.128.160
32,768.0
tensor
4 $1.26 4.171 Launch
rtx3090-2.16.64.160
32,768.0
tensor
2 $1.56 72.520 3.541 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 1.673 Launch
rtx3080-4.16.64.160
32,768.0
tensor
4 $1.82 1.110 Launch
rtx4090-2.16.64.160
32,768.0
tensor
2 $1.92 3.529 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 76.570 9.018 Launch
h100-1.16.64.160
32,768.0
1 $3.83 64.970 9.007 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 109.540 11.140 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 20.619 Launch
h200-1.16.128.160
32,768.0
1 $4.74 18.302 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 39.188 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa10-2.16.64.160
32,768.0
tensor
2 $0.93 1.215 Launch
teslat4-4.16.64.160
32,768.0
tensor
4 $0.96 2.145 Launch
rtxa5000-2.16.64.160.nvlink
32,768.0
tensor
2 $1.23 1.215 Launch
teslaa2-4.32.128.160
32,768.0
tensor
4 $1.26 2.169 Launch
rtx3090-2.16.64.160
32,768.0
tensor
2 $1.56 1.540 Launch
rtx4090-2.16.64.160
32,768.0
tensor
2 $1.92 1.528 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 7.016 Launch
rtx5090-2.16.64.160
32,768.0
tensor
2 $2.93 3.929 Launch
h100-1.16.64.160
32,768.0
1 $3.83 7.006 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 9.139 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 18.618 Launch
h200-1.16.128.160
32,768.0
1 $4.74 16.301 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 37.187 Launch

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