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Model garden Router · on request Dedicated · available

Qwen3 32B

Runs as your own dedicated GPU deployment, ready to launch from the wizard. Data stays in Europe.

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities,...

Start for free ← All models
Qwen/Qwen3-32B 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
33B
Parameters
41K
Context window
80GB
Minimum VRAM
POST /api/v1/chat/completions On request

Specifications

Parameters 33B
Context window 40,960 tokens
Minimum VRAM 80 GB
Architecture Qwen3ForCausalLM (vLLM)
License apache-2.0
Modality text->text
Released April 2025
Publisher Qwen ↗

Pricing

Shared router · per token
On request
Not available on the shared router. Pricing on request as a dedicated GPU deployment.
Dedicated GPU · per hour
from €1,08 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 29-07-2026, responded in 741 ms on our EU infrastructure.

Bench index

Bench is our quality index for every model, 0 to 100. It rests on public measurements (Epoch AI with about 40 benchmarks, LiveBench, LMArena and more) and is refreshed every morning. Where nobody measures, it shows an estimate with a range.

60.5 / 100 · Measured

Measured by Epoch AI across 6 benchmarks, with a range.

Range 55.9 to 62.8 · Rank 131 of 270 at Epoch AI

Sources: Epoch AI ↗ · LiveBench ↗ · LMArena ↗ · Refreshed daily, last on 24-10-2026

LiveBench · 43.6
Reasoning 48.3
Coding 66.0
Agentic coding 3.3
Mathematics 67.4
Data analysis 46.5
Language 55.5
Instruction following 17.8
Every benchmark (6)
Fiction.LiveBench 74.2
OTIS Mock AIME 2024-2025 66.9
GPQA diamond 56.6
DTBench 45.8
Aider polyglot 40.0
LMCA 20.3
LiveBench · All tasks
Reasoning
theory of mind 55.8
zebra puzzle 21.3
spatial 86.0
logic with navigation 30.0
Coding
code generation 69.0
code completion 63.0
Agentic coding
javascript 0.0
typescript 0.0
python 10.0
Mathematics
AMPS Hard 87.0
integrals with game 25.0
math comp 84.3
olympiad 73.5
Data analysis
consecutive events 3.0
tablejoin 38.5
tablereformat 98.0
Language
connections 61.0
plot unscrambling 37.6
typos 68.0
Instruction following
paraphrase 15.8
simplify 20.1
story generation 14.5
summarize 20.7

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/Qwen3-32B",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Frequently asked questions

Can I run Qwen3 32B in the EU?

Yes. HostYourAI runs Qwen3 32B 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 32B 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 32B cost?

Qwen3 32B is available on request: through the shared EU router after a quick chat, or as your own dedicated GPU deployment billed per hour. Tell us your use case and we will set it up for you.

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

Qwen Image 2.1 Turbo

Qwen-Image-2.1-Turbo is an accelerated checkpoint of Qwen-Image-2.1 for text-to-image generation and image editing with 8 denoising steps. It uses the same 7B visual generation architecture and loads directly with QwenImage21Pipeline in Diffusers.

7.1B View model →
Qwen Image 2.1 PE T2I

We are excited to open-source Qwen-Image-2.1, a unified text-to-image generation and image editing model in the Qwen family. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Qwen-Image-2.1 balances generation quality, inference efficiency, and versatility.

9.4B 262K context View model →
Qwen Image 2.1

We are excited to open-source Qwen-Image-2.1, a unified text-to-image generation and image editing model in the Qwen family. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Qwen-Image-2.1 balances generation quality, inference efficiency, and versatility.

7.1B View model →
Qwen3.8 Flash Next

[!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.

180B 262K context View model →
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 →

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