Expired50% confidenceBenchmarkExact time
A dual 24GB GPU tensor-parallel configuration increases context support from 134,049 to 262,144 tokens at f16 precision.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/7/2026
First Seen
Valid until: 10/5/2026(expired)
Sources
Related Claims
UnverifiedA 35B model requires approximately 70GB of VRAM at FP16 precision, far exceeding the RTX 5090's 32GB capacity, so single-GPU deployment requires quantization.74% similarUnverifiedUP主使用FP8精度部署千问3.8 27B在48GB显卡上，跑4个并发request占用约46GB72% similarUnverifiedEven compressing the weights to 214GB using 4-bit quantization still far exceeds the capacity of a single 48GB GPU.71% similarVerified以LLaMA-3 70B（80层、64头、每头128维）为例，单个token的KV Cache约占2.6MB（FP16精度），32K上下文的KV Cache总量约达83GB71% similar
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