Can I run it?
Can I run Sharp Spark X2.5 4B on NVIDIA H100 SXM 80GB?
Runs great
Runs great fully on your NVIDIA H100 SXM 80GB at Q6_K, 8K context, about 382–521 tok/s. Weights 3.36 GB plus 0.33 GB of KV cache — 4.03 GB of 76.0 GB usable. Up to 1024K context still fits.
Best quantQ6_K
Working context8K
Max that fits1024K
Speed382–521 tok/sEstimate from memory bandwidth, not a benchmark. Method.
Weights3.36 GB
KV cache0.33 GB
Total4.03 GB
Usable76.0 GB
Sharp Spark X2.5 4B details · NVIDIA H100 SXM 80GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf peculiar-ragdoll/Sharp-Spark-X2.5-4B-GGUF:Q6_K -c 8192 -ngl 36
No matching name in the Ollama library snapshot.
LM Studio
lms get peculiar-ragdoll/Sharp-Spark-X2.5-4B-GGUF # Then load quant Q6_K
Assumptions
- Estimate from memory bandwidth, not a benchmark. Decode speed uses 55–75% of peak bandwidth.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- Q6_K size is the real GGUF file size from Hugging Face.
- CPU runs keep about 4 GB plus a 10% cushion for the OS.
- Speed is quoted at 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on NVIDIA H100 SXM 80GB? — Runs, BF16, 33–46 tok/s (estimate)
- Can I run gemma 4 12b it on NVIDIA H100 SXM 80GB? — Runs great, BF16, 68–93 tok/s (estimate)
- Can I run Qwen3.5 9B on NVIDIA H100 SXM 80GB? — Runs great, BF16, 101–138 tok/s (estimate)
Updated 2026-10-24. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.