Unverified50% confidenceBenchmarkExact time
The Q8 main model occupies 162 GB, preventing the drafter from fitting into unified memory, rendering DSpark acceleration ineffective; after moving three layers of MoE experts back to the CPU, output only improved from 22.87 to 23.49 tokens/second (2.7% faster), while prefill dropped from 95.38 to 76.65.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/11/2026
First Seen
Valid until: 12/10/2026
Sources
Related Entities
Related Claims
UnverifiedWhen model weights and KV Cache cannot be fully loaded into GPU VRAM and some data must be offloaded to main memory, inference speed drops by one to two orders of magnitude.68% similarUnverifiedIn the DeepSeek V4 (D300 machine) test scenario with 8K input/1K output, DSpark achieves a single-user token rate improvement of nearly 150x compared to the baseline.67% similarUnverifiedvLLM compresses the KV Cache memory fragmentation rate from above 60% to near zero through PagedAttention technology, and can increase inference throughput by several times in high-concurrency scenarios.66% similar
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