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

API access to Qwen2.5-1.5B-Instruct endpoints

There are no public endpoints for this model yet.

Private endpoint

An endpoint is a server with pre-installed software that automatically downloads neural network weights and launches an OpenAI-compatible API to handle incoming requests.

A private endpoint is created within the user's project, belongs exclusively to the user, and is billed per server configuration in accordance with the infrastructure pricing.

We recommend creating private endpoints when you need to:

  • achieve maximum endpoint performance,
  • access the full context window for processing large requests and conversations,
  • ensure maximum security by processing data in a dedicated, isolated environment.

Recommended server configurations for creating a private inference endpoint Qwen2.5-1.5B-Instruct

Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-1.16.32.160
32,768.0
1 $0.38 98.80 10.218 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 215.29 18.525 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 265.76 4.972 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 500.00 22.235 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 548.00 19.597 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 40.502 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 27.830 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 172.70 78.193 Launch
h100-1.16.64.160
32,768.0
1 $3.83 548.00 78.120 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 436.00 92.745 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 157.610 Launch
h200-1.16.128.160
32,768.0
1 $4.74 141.857 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 284.938 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-1.16.32.160
32,768.0
1 $0.38 75.11 11.831 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 172.50 20.069 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 218.22 6.607 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 139.97 21.549 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 239.40 21.072 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 44.538 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 29.465 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 231.33 79.669 Launch
h100-1.16.64.160
32,768.0
1 $3.83 220.17 79.389 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 232.75 93.992 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 161.646 Launch
h200-1.16.128.160
32,768.0
1 $4.74 143.493 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 288.974 Launch
Prices:
Name GPU Price, hour TPS Max Concurrency
teslaa2-1.16.32.160
32,768.0
1 $0.38 46.95 10.802 Launch
teslaa10-1.16.32.160
32,768.0
1 $0.53 109.65 19.109 Launch
rtx3080-1.16.32.160
32,768.0
1 $0.57 153.08 5.556 Launch
rtx3090-1.16.24.160
32,768.0
1 $0.83 164.24 20.223 Launch
rtx4090-1.16.32.160
32,768.0
1 $1.02 197.84 20.181 Launch
rtx3090-2.16.64.160.nvlink
32,768.0
tensor
2 $1.56 43.852 Launch
rtx5090-1.16.64.160
32,768.0
1 $1.59 28.414 Launch
teslaa100-1.16.64.160
32,768.0
1 $2.37 178.35 78.663 Launch
h100-1.16.64.160
32,768.0
1 $3.83 78.704 Launch
h100nvl-1.16.96.160
32,768.0
1 $4.11 93.329 Launch
teslaa100-2.24.96.160.nvlink
32,768.0
tensor
2 $4.61 160.960 Launch
h200-1.16.128.160
32,768.0
1 $4.74 142.441 Launch
h200-2.24.256.160.nvlink
32,768.0
tensor
2 $9.40 288.288 Launch

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

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