Expired50% confidenceDecision RuleExact time
When running the Qwen3 conversational model, 8GB of VRAM supports the 1.7B/6B parameter versions, while 12GB/16GB/24GB of VRAM supports larger parameter versions.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/22/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/20/2026(expired)
Sources
Cherry Studio+MCP+Ollama本地AI智能体搭建全教程
Related Claims
Unverified8GB of VRAM is sufficient to run Q4/Q5 quantized versions of 7B models (all layers on GPU), while 12GB of VRAM can run Q4 quantized versions of 14B models or Q8 versions of 7B models.72% similarUnverifiedQwen3-27B was officially released with a quantized model in GGUF format, enabling local deployment with a minimum of 8GB of VRAM.72% similarUnverifiedThe Qwen3.6 27B parameter version supports a maximum context window of 128K.71% similarUnverifiedThe Qwen 3.6 27B FP8 model was successfully deployed locally on a 4×3080Ti 16GB GPU.70% similarUnverifiedFor 8 GB VRAM, Llama 3.1 8B Instruct, Qwen2.5 7B Instruct, and Mistral 7B with Q4_K_M quantization are recommended.70% similar
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