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Qwen2.5 14B Instruct AWQ

Direct via de EU-router of als dedicated GPU-deployment. Data blijft in Europa.

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:

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Qwen/Qwen2.5-14B-Instruct-AWQ
text->text · Qwen · EU-hosted
15B
Parameters
33K
Contextvenster
34GB
Minimale VRAM
POST /api/v1/chat/completions200 OK

Specificaties

Parameters 15B
Contextvenster 32,768 tokens
Minimale VRAM 34 GB
Architectuur Qwen2ForCausalLM (vLLM)
Licentie apache-2.0
Modaliteit text->text
Uitgebracht September 2024
Uitgever Qwen ↗

Prijzen

€0.15
Input (per 1M tokens)
€0.25
Output (per 1M tokens)

Gedeelde EU-router, pay-per-token, scale-to-zero. Dedicated GPU-deployments worden per uur afgerekend — zie prijzen.

Direct aanroepen

Drop-in vervanger voor OpenAI: wijzig alleen de base-URL en de API-key. Ook het Anthropic-formaat (/v1/messages) wordt ondersteund.

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!"}]
  }'

Veelgestelde vragen

Kan ik Qwen2.5 14B Instruct AWQ in de EU draaien?

Ja. HostYourAI draait Qwen2.5 14B Instruct AWQ op GPU's in Europese datacenters via vLLM. Prompts en outputs verlaten de EU niet en er is geen Amerikaanse cloudprovider in de keten.

Is Qwen2.5 14B Instruct AWQ hosten AVG/GDPR-compliant?

Ja. Alle verwerking vindt plaats binnen de EU, er is een verwerkersovereenkomst (DPA) beschikbaar en de subprocessor-lijst is openbaar. Open-source gewichten betekenen ook: geen training op jouw data.

Wat kost Qwen2.5 14B Instruct AWQ?

Via de gedeelde EU-router betaal je €0.15 per miljoen input-tokens en €0.25 per miljoen output-tokens, zonder vaste kosten. Voor hoge volumes of isolatie kun je Qwen2.5 14B Instruct AWQ ook als dedicated GPU-instance per uur draaien.

Is de API compatibel met OpenAI?

Ja. Je gebruikt de standaard OpenAI-SDK's met een aangepaste base-URL (https://hostyourai.com/api/v1). Ook de Anthropic Messages API wordt ondersteund als drop-in.

Andere modellen van Qwen

Qwen3.6 27B FP8

[!Note] This repository contains FP8-quantized 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. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model.

28B Bekijk 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 Bekijk model →
Qwen3.6 35B A3B FP8

[!Note] This repository contains FP8-quantized 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. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model.

36B Bekijk 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 Bekijk model →
Qwen3.5 35B A3B GPTQ Int4

[!Note] This repository contains int4-quantized 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 Bekijk model →
Qwen3.5 27B GPTQ Int4

[!Note] This repository contains int4-quantized 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 Bekijk model →

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