SourceReddit r/LocalLLaMA•Stalecollected in 6h
NVIDIA Puzzle-Optimized 88B LLM
#moe#nas#h100#inferencegpt-oss-puzzle-88bnvidiagpt-oss-puzzle-88bgpt-oss-120bpuzzle-nas
💡NVIDIA's 88B model: 1.63x faster long-context on H100s, same accuracy
⚡ 30-Second TL;DR
What Changed
88B params (73% of 120B parent)
Why It Matters
Enhances efficient serving of reasoning LLMs on H100 clusters, addressing KV-cache limits for production deployment.
What To Do Next
Deploy gpt-oss-puzzle-88B on Hugging Face and test long-context throughput on H100.
Who should care:Enterprise & Security Teams
Key Points
- •88B params (73% of 120B parent)
- •1.63x throughput long-context (64K) on 8x H100
- •2.82x single H100 throughput gain
- •MoE transformer with modified attention
- •Matches/exceeds parent reasoning accuracy
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Original source: Reddit r/LocalLLaMA ↗
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