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Qwen2.5 14B Instruct AWQ

Instantly via the EU router or as a dedicated GPU deployment. Data stays in Europe.

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:

Start for free ← All models
Qwen/Qwen2.5-14B-Instruct-AWQ vLLM ready
text->text · Qwen · sovereign EU
Runs on EU infrastructure operated by European companies; US marketplace capacity is never part of this chain. Full chain
15B
Parameters
33K
Context window
80GB
Minimum VRAM
POST /api/v1/chat/completions 200 OK

Specifications

Parameters 15B
Context window 32,768 tokens
Minimum VRAM 80 GB
Architecture Qwen2ForCausalLM (vLLM)
License apache-2.0
Modality text->text
Released September 2024
Publisher Qwen ↗

Pricing

Shared router · per token
€0.08
Input (per 1M tokens)
€0.25
Output (per 1M tokens)
Dedicated GPU · per hour
from €1,05 per hour
Your own vLLM instance on European cloud (80 GB VRAM), billed hourly.

Shared EU router, pay-per-token, scale-to-zero. Dedicated GPU deployments are billed hourly, see pricing.

✓ Verified working on 26-07-2026, responded in 153 ms on our EU infrastructure.

Call it now

Drop-in replacement for OpenAI: change only the base URL and API key. The Anthropic format (/v1/messages) is supported too.

curl https://hostyourai.com/api/v1/chat/completions \
  -H "Authorization: Bearer hyai-..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen2.5-14B-Instruct-AWQ",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Frequently asked questions

Can I run Qwen2.5 14B Instruct AWQ in the EU?

Yes. HostYourAI runs Qwen2.5 14B Instruct AWQ on GPUs in European datacenters via vLLM. Prompts and outputs never leave the EU and there is no US cloud provider in the chain.

Is hosting Qwen2.5 14B Instruct AWQ GDPR-compliant?

Yes. All processing happens inside the EU, a Data Processing Agreement (DPA) is available and the subprocessor list is public. Open-source weights also mean: no training on your data.

How much does Qwen2.5 14B Instruct AWQ cost?

Via the shared EU router you pay €0.08 per million input tokens and €0.25 per million output tokens, with no fixed costs. For high volume or isolation you can also run Qwen2.5 14B Instruct AWQ as a dedicated hourly GPU instance.

Is the API OpenAI-compatible?

Yes. You use the standard OpenAI SDKs with a custom base URL (https://hostyourai.com/api/v1). The Anthropic Messages API is supported as a drop-in as well.

More models from Qwen

Qwen3.8 27B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.

28B 262K context View model →
Qwen3 ASR 0.6B hf

The Qwen3-ASR family includes Qwen3-ASR-1.7B and Qwen3-ASR-0.6B, which support language identification and ASR for 52 languages and dialects. Both leverage large-scale speech training data and the strong audio understanding capability of their foundation model, Qwen3-Omni. The 1.7B version achieves state-of-the-art performance among open-source ASR models and is competitive with the strongest proprietary commercial APIs.

0.8B 66K context View model →
Qwen3 ASR 1.7B hf

The Qwen3-ASR family includes Qwen3-ASR-1.7B and Qwen3-ASR-0.6B, which support language identification and ASR for 52 languages and dialects. Both leverage large-scale speech training data and the strong audio understanding capability of their foundation model, Qwen3-Omni. The 1.7B version achieves state-of-the-art performance among open-source ASR models and is competitive with the strongest proprietary commercial APIs.

2B 66K context View model →
Qwen3.6 27B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

28B 262K context View model →
Qwen3.6 35B A3B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

36B 262K context View model →
Qwen3.5 0.8B

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. In light of its parameter scale, the intended use cases are prototyping, task-specific fine-tuning, and other research or development purposes.

0.9B 262K context View model →

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