L
localai.computer
ModelsGPUsSystemsAI SetupsBuildsOpenClawMethodology

Resources

  • Methodology
  • Submit Benchmark
  • About

Browse

  • AI Models
  • GPUs
  • PC Builds

Guides

  • OpenClaw Guide
  • How-To Guides

Legal

  • Privacy
  • Terms
  • Contact

© 2025 localai.computer. Hardware recommendations for running AI models locally.

ℹ️We earn from qualifying purchases through affiliate links at no extra cost to you. This supports our free content and research.

Can NVIDIA H100 SXM5 80GB run HuggingFaceTB/SmolLM-135M?

Runs Q480GB VRAM availableRequires 4GB+

NVIDIA H100 SXM5 80GB meets the minimum VRAM requirement for Q4 inference of HuggingFaceTB/SmolLM-135M. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

NVIDIA H100 SXM5 80GB can run HuggingFaceTB/SmolLM-135M with Q4 quantization. At approximately 508 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 76GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q44GB80GB508.15 tok/s✅ Fits comfortably
Q87GB80GB332.40 tok/s✅ Fits comfortably
FP1615GB80GB206.34 tok/s✅ Fits comfortably

Suitable alternatives

AMD Instinct MI300X
192GB
803.68 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
689.37 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
523.43 tok/s
Price: —
AMD Instinct MI300X
192GB
486.54 tok/s
Price: —
AMD Instinct MI250X
128GB
441.76 tok/s
Price: —

More questions

NVIDIA H100 SXM5 80GB specs & pricingFull guide for HuggingFaceTB/SmolLM-135MHuggingFaceTB/SmolLM-135M speed on NVIDIA H100 SXM5 80GBHuggingFaceTB/SmolLM-135M Q4 requirements