Unverified50% confidenceFactExact time
Local deployment of the 2.4-trillion-parameter Qwen3.8 requires approximately 1.4–1.5 TB of GPU memory, necessitating quantization or a multi-GPU cluster.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/24/2026
First Seen
Valid until: 10/22/2026
Sources
Related Claims
UnverifiedQwen2 0.5B模型（5亿参数）运行仅需约352MB显存77% similarUnverifiedModels in the 3B–4B range, such as Qwen2.5 3B or Llama 3.2 3B, require only 2 to 2.5GB of VRAM under Q4 quantization.76% similarVerifiedAlibaba launched Qwen 3.6 35B A3B, a Mixture-of-Experts model with 35 billion parameters, of which only 3 billion are active at any given time; the approximately 72 GB weights have been open-sourced on Hugging Face.75% similarUnverifiedQwen3-series coding models load at approximately 20 GB and can expand to 35–40 GB during inference.75% similarVerifiedQLoRA introduces 4-bit quantization technology, making it possible to fine-tune models with 65 billion parameters on a single RTX 3090/4090 GPU with 24 GB of VRAM.74% similar
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