Model garden

Qwen3 4B Instruct 2507 FP8

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

We introduce the updated version of the Qwen3-4B-FP8 non-thinking mode, named Qwen3-4B-Instruct-2507-FP8, featuring the following key enhancements:

Qwen/Qwen3-4B-Instruct-2507-FP8 vLLM ready
text->text · Qwen · EU-hosted
4.4B
Parameters
262K
Contextvenster
11GB
Minimale VRAM
POST /api/v1/chat/completions200 OK

Specificaties

Parameters 4.4B
Contextvenster 262,144 tokens
Minimale VRAM 11 GB
Architectuur Qwen3ForCausalLM (vLLM)
Licentie apache-2.0
Modaliteit text->text
Uitgebracht August 2025
Uitgever Qwen ↗

Prijzen

€0.05
Input (per 1M tokens)
€0.10
Output (per 1M tokens)

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

✓ Werkend geverifieerd op 24-06-2026 — respons in 1882 ms op onze EU-infrastructuur.

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/Qwen3-4B-Instruct-2507-FP8",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Veelgestelde vragen

Kan ik Qwen3 4B Instruct 2507 FP8 in de EU draaien?

Ja. HostYourAI draait Qwen3 4B Instruct 2507 FP8 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 Qwen3 4B Instruct 2507 FP8 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 Qwen3 4B Instruct 2507 FP8?

Via de gedeelde EU-router betaal je €0.05 per miljoen input-tokens en €0.10 per miljoen output-tokens, zonder vaste kosten. Voor hoge volumes of isolatie kun je Qwen3 4B Instruct 2507 FP8 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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