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Model garden Router · available Dedicated · available

Qwen3.6 27B FP8

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

Qwen3.6 27B FP8 is an open-source language model from Qwen with 27B parameters and a 262K-token context window, hosted on EU GPUs via an OpenAI-compatible API.

Start for free ← All models
qwen3.6-27b-fp8 vLLM ready
text->text · qwen · EU-hosted
27B
Parameters
262K
Context window
48GB
Minimum VRAM
POST /api/v1/chat/completions 200 OK

Specifications

Parameters 27B
Context window 262,144 tokens
Minimum VRAM 48 GB
License open-weights
Modality text->text
Publisher qwen ↗

Pricing

Shared router · per token
€0.08
Input (per 1M tokens)
€0.25
Output (per 1M tokens)
Dedicated GPU · per hour
from €2,22 per hour
Your own vLLM instance on European cloud (48 GB VRAM), billed hourly.

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

✓ Verified working on 21-07-2026, responded in 1388 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": "qwen3.6-27b-fp8",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Frequently asked questions

Can I run Qwen3.6 27B FP8 in the EU?

Yes. HostYourAI runs Qwen3.6 27B FP8 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 Qwen3.6 27B FP8 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 Qwen3.6 27B FP8 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 Qwen3.6 27B FP8 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

Qwen3.6 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 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 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 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 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 View 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 View model →

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