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 RTX 6000 Ada run Qwen/Qwen2.5-14B-Instruct?

Runs Q448GB VRAM availableRequires 8GB+

NVIDIA RTX 6000 Ada meets the minimum VRAM requirement for Q4 inference of Qwen/Qwen2.5-14B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

NVIDIA RTX 6000 Ada can run Qwen/Qwen2.5-14B-Instruct with Q4 quantization. At approximately 121 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 40GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q48GB48GB121.44 tok/s✅ Fits comfortably
Q815GB48GB95.02 tok/s✅ Fits comfortably
FP1630GB48GB49.19 tok/s✅ Fits comfortably

Best current price

NVIDIA RTX 6000 Ada
$7,199.00 on Amazon
Check Price

Suitable alternatives

AMD Instinct MI300X
192GB
549.54 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
539.79 tok/s
Price: —
AMD Instinct MI300X
192GB
439.84 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
374.83 tok/s
Price: —
AMD Instinct MI250X
128GB
367.79 tok/s
Price: —

More questions

NVIDIA RTX 6000 Ada specs & pricingFull guide for Qwen/Qwen2.5-14B-InstructQwen/Qwen2.5-14B-Instruct speed on NVIDIA RTX 6000 AdaQwen/Qwen2.5-14B-Instruct Q4 requirements