Verified80% confidenceFactExact time
NVIDIA claims that the weights of Nemotron 3.5 Bolt 74B-A9B can run in 24GB of memory, and that 24GB refers only to the weights themselves, excluding context, KV cache and runtime overhead.
4
Sources
80%
Confidence
Medium-term (~90 days)
Relevance
10/15/2026
First Seen
Valid until: 1/13/2027
Sources
Related Entities
Related Claims
UnverifiedNemotron Bolt 3.5 74B A9B uses 2-bit quantization combined with quantization-aware training (QAT) to compress the entire model to about 24GB of VRAM usage.74% similarUnverifiedAn NVIDIA H100 single card has 80 GB of VRAM, and an 8-card node with 640 GB is still insufficient to load the full weights of Qwen3.8.73% similarVerifiedNVIDIA's upcoming RTX Spark laptop offers up to 128 GB of unified memory in its highest configuration.73% similarUnverifiedM3 Max 配备最高 128GB 统一内存，可运行未量化的 70B 甚至更大规模模型，远超消费级 NVIDIA 显卡最高 24GB 的上限72% similarUnverifiedThe NVIDIA A100 has a memory bandwidth of 2 TB/s; loading a 280 GB FP32 model takes approximately 140 ms, meaning weight loading alone limits generation to a maximum of approximately 7 tokens per second.72% similar
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