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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.
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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.
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Model Name
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Size (4-bit Quantization)
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Recommended GPUs
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Tokens/s
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| 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 |
| qwen3:32bqwen2.5:32b | 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 |
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.
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Model Name
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