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 RX 7900 XTX run meta-llama/Llama-3.1-8B?

Runs Q424GB VRAM availableRequires 4GB+

RX 7900 XTX meets the minimum VRAM requirement for Q4 inference of meta-llama/Llama-3.1-8B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

RX 7900 XTX can run meta-llama/Llama-3.1-8B with Q4 quantization. At approximately 149 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 20GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q44GB24GB149.45 tok/s✅ Fits comfortably
Q89GB24GB102.51 tok/s✅ Fits comfortably
FP1617GB24GB60.68 tok/s✅ Fits comfortably

Best current price

RX 7900 XTX
$899.00 on Amazon
Check Price

Suitable alternatives

AMD Instinct MI300X
192GB
810.24 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
666.36 tok/s
Price: —
AMD Instinct MI300X
192GB
550.08 tok/s
Price: —
AMD Instinct MI250X
128GB
524.41 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
505.82 tok/s
Price: —

More questions

RX 7900 XTX specs & pricingFull guide for meta-llama/Llama-3.1-8Bmeta-llama/Llama-3.1-8B speed on RX 7900 XTXmeta-llama/Llama-3.1-8B Q4 requirements