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 RTX 5090 run meta-llama/Llama-3.1-70B-Instruct?

Q4 not recommended32GB VRAM availableRequires 34GB+

RTX 5090 does not meet the minimum VRAM requirement for Q4 inference of meta-llama/Llama-3.1-70B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

RTX 5090 lacks sufficient VRAM for comfortable meta-llama/Llama-3.1-70B-Instruct operation with Q4 quantization.

Your 32GB GPU is 2GB short of the 34GB minimum.

Options: (1) Try Q2 or Q3 quantization for lower VRAM requirements, (2) Consider cloud GPU rental, (3) Upgrade to a GPU with at least 16GB VRAM.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q434GB32GB64.97 tok/s❌ Not recommended
Q869GB32GB41.65 tok/s❌ Not recommended
FP16138GB32GB21.35 tok/s❌ Not recommended

Suitable alternatives

AMD Instinct MI300X
192GB
160.26 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
127.91 tok/s
Price: —
AMD Instinct MI300X
192GB
115.04 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
95.14 tok/s
Price: —
AMD Instinct MI250X
128GB
94.63 tok/s
Price: —

More questions

RTX 5090 specs & pricingFull guide for meta-llama/Llama-3.1-70B-Instructmeta-llama/Llama-3.1-70B-Instruct speed on RTX 5090meta-llama/Llama-3.1-70B-Instruct Q4 requirements