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 PCIe 80GB run meta-llama/Llama-3.3-70B-Instruct?

Runs Q480GB VRAM availableRequires 34GB+

NVIDIA H100 PCIe 80GB meets the minimum VRAM requirement for Q4 inference of meta-llama/Llama-3.3-70B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

NVIDIA H100 PCIe 80GB can run meta-llama/Llama-3.3-70B-Instruct with Q4 quantization. At approximately 111 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 46GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q434GB80GB111.37 tok/s✅ Fits comfortably
Q868GB80GB84.32 tok/s✅ Fits comfortably
FP16137GB80GB44.30 tok/s❌ Not recommended

Suitable alternatives

AMD Instinct MI300X
192GB
278.82 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
257.02 tok/s
Price: —
AMD Instinct MI300X
192GB
190.32 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
185.52 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
181.44 tok/s
Price: —

More questions

NVIDIA H100 PCIe 80GB specs & pricingFull guide for meta-llama/Llama-3.3-70B-Instructmeta-llama/Llama-3.3-70B-Instruct speed on NVIDIA H100 PCIe 80GBmeta-llama/Llama-3.3-70B-Instruct Q4 requirements