Model garden Router · beschikbaar Dedicated · op aanvraag

Qwen3 Coder 30B A3B Instruct FP8

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

Qwen3-Coder is available in multiple sizes. Today, we're excited to introduce Qwen3-Coder-30B-A3B-Instruct-FP8. This streamlined model maintains impressive performance and efficiency, featuring the following key enhancements:

Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8 vLLM ready
text->text · Qwen · EU-hosted
31B
Parameters
262K
Contextvenster
48GB
Minimale VRAM
POST /api/v1/chat/completions 200 OK

Specificaties

Parameters 31B
Contextvenster 262,144 tokens
Minimale VRAM 48 GB
Architectuur Qwen3MoeForCausalLM (vLLM)
Licentie apache-2.0
Modaliteit text->text
Uitgebracht July 2025
Uitgever Qwen ↗

Prijzen

Gedeelde router · per token
€0.08
Input (per 1M tokens)
€0.25
Output (per 1M tokens)
Dedicated GPU · per uur
Op aanvraag
Dedicated deployment, vanaf 48 GB VRAM. Afgerekend per GPU-uur.

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

✓ Werkend geverifieerd op 21-07-2026, respons in 2972 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-Coder-30B-A3B-Instruct-FP8",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Veelgestelde vragen

Kan ik Qwen3 Coder 30B A3B Instruct FP8 in de EU draaien?

Ja. HostYourAI draait Qwen3 Coder 30B A3B Instruct 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 Coder 30B A3B Instruct 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 Coder 30B A3B Instruct FP8?

Via de gedeelde EU-router betaal je €0.08 per miljoen input-tokens en €0.25 per miljoen output-tokens, zonder vaste kosten. Voor hoge volumes of isolatie kun je Qwen3 Coder 30B A3B Instruct 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 262K context 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 262K context 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 262K context 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 262K context 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 262K context Bekijk model →
Qwen3.5 0.8B Base

[!Note] This repository contains model weights and configuration files for the pre-trained only model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, etc. The intended use cases are fine-tuning, in-context learning experiments, and other research or development purposes, not direct interaction. However, the control tokens, e.g., <|imstart| and <|imend| were trained to allow efficient LoRA-style PEFT with the official chat template, mitigating the need to finetune embeddings, a significant optimization given Qwen3.5's larger

0.9B 262K context Bekijk model →

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