Qwen Hosting | Private Alibaba Qwen LLM Deployment on GPU – B2BHostingClub

Celebrate 79 Years of Freedom with 79% OFF on All Shared Hosting Plans! 🇵🇰

Pre-installed Qwen3-32B LLM Hosting

B2BHOSTINGCLUB offers best budget GPU servers for Qwen3 LLMs. You'll get pre-installed Open WebUI + Ollama + Qwen3-32B, it is a popluar way to self-hosted LLM models.

Advanced GPU Dedicated Server - A5000

/mo

  • 128GB RAM
  • GPU: Nvidia Quadro RTX A5000
  • Dual 12-Core E5-2697v2
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ampere
  • CUDA Cores: 8192
  • Tensor Cores: 256
  • GPU Memory: 24GB GDDR6
  • FP32 Performance: 27.8 TFLOPS

Enterprise GPU Dedicated Server - RTX 4090

/mo

  • 256GB RAM
  • GPU: GeForce RTX 4090
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Linux / Windows 10/11
  • Single GPU Specifications:
  • Microarchitecture: Ada Lovelace
  • CUDA Cores: 16,384
  • Tensor Cores: 512
  • GPU Memory: 24 GB GDDR6X
  • FP32 Performance: 82.6 TFLOPS

Advanced GPU VPS - RTX 5090

/mo

  • 96GB RAM
  • Dedicated GPU: GeForce RTX 5090
  • 32 CPU Cores
  • 400GB SSD
  • 500Mbps Unmetered Bandwidth
  • OS: Linux / Windows 10/11
  • Once per 2 Weeks Backup
  • Single GPU Specifications:
  • CUDA Cores: 21,760
  • Tensor Cores: 680
  • GPU Memory: 32GB GDDR7
  • FP32 Performance: 109.7 TFLOPS

Enterprise GPU Dedicated Server - A100

/mo

  • 256GB RAM
  • GPU: Nvidia A100
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • Single GPU Microarchitecture: Ampere
  • CUDA Cores: 6912
  • Tensor Cores: 432
  • GPU Memory: 40GB HBM2
  • FP32 Performance: 19.5 TFLOPS

Ollama Qwen Hosting Service GPU Recommendation

Qwen Hosting with Ollama provides a streamlined environment for running Qwen large language models using the Ollama framework — a user-friendly platform that simplifies local LLM deployment and inference.

Model Name
Size (4-bit Quantization)
Recommended GPUs
Tokens/s
qwen3:0.6b 523MB P1000 ~54.78
qwen3:1.7b 1.4GB P1000 < T1000 < GTX1650 < GTX1660 < RTX2060 25.3-43.12
qwen3:4b 2.6GB T1000 < GTX1650 < GTX1660 < RTX2060 < RTX5060 26.70-90.65
qwen2.5:7b 4.7GB T1000 < RTX3060 Ti < RTX4060 < RTX5060 21.08-62.32
qwen3:8b 5.2GB T1000 < RTX3060 Ti < RTX4060 < A4000 < RTX5060 20.51-62.01
qwen3:14b 9.3GB A4000 < A5000 < V100 30.05-49.38
qwen3:30b 19GB A5000 < RTX4090 < A100-40gb < RTX5090 28.79-45.07
qwen3:32b
qwen2.5:32b
20GB A5000 < RTX4090 < A100-40gb < RTX5090 24.21-45.51
qwen2.5:72b 47GB 2*A100-40gb < A100-80gb < H100 < 2*RTX5090 19.88-24.15
qwen3:235b 142GB 4*A100-40gb < 2*H100 ~10-20

vLLM Qwen Hosting Service
GPU Recommendation

Qwen Hosting with vLLM + Hugging Face delivers an optimized server environment for running Qwen large language models using the high-performance vLLM inference engine, seamlessly integrated with the Hugging Face Transformers ecosystem.

Model Name