Unverified50% confidenceBenchmarkExact time
Under fp32, PreCap's CUDA kernel runs at about within 1.5× the speed of native SELU.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/27/2026
First Seen
Valid until: 1/25/2027
Sources
Related Entities
Related Claims
UnverifiedIn a pure-CPU environment, comparing llama.cpp build 9976 and build 11571 running the same Gemma quantised model, the new build's generation speed is about 9.1% faster than the old build (6.60 vs 6.05 tok/s).67% similarUnverified配备NVIDIA GPU并使用CUDA加速，7B模型可以达到50-100+ token/s的推理速度67% similarUnverifiedMagnitude's CUDA kernel autotuning activates the RTX 4090's Tensor Cores for INT4 operations, which is one of the keys to its doubled throughput.65% similarUnverifiedThe Fast Start feature in v0.30.0 saves quantized, tensor-parallel-sharded weights in a per-GPU resident daemon process and maps them directly via CUDA IPC on restart, enabled with --load-format ipc_cache.64% similarVerifiedThe NVIDIA A100 has 6,912 CUDA cores and 432 Tensor Cores, with a theoretical peak compute of 312 TFLOPS (BF16).64% similar
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