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 4090 run Qwen/Qwen2.5-7B-Instruct?

Runs Q424GB VRAM availableRequires 4GB+

RTX 4090 meets the minimum VRAM requirement for Q4 inference of Qwen/Qwen2.5-7B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

RTX 4090 can run Qwen/Qwen2.5-7B-Instruct with Q4 quantization. At approximately 186 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
Q44GB24GB185.68 tok/s✅ Fits comfortably
Q88GB24GB126.86 tok/s✅ Fits comfortably
FP1616GB24GB62.97 tok/s✅ Fits comfortably

Best current price

RTX 4090
$1,599.00 on Amazon
Check Price

Suitable alternatives

AMD Instinct MI300X
192GB
830.07 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
735.38 tok/s
Price: —
AMD Instinct MI300X
192GB
585.07 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
485.90 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
481.50 tok/s
Price: —

More questions

RTX 4090 specs & pricingFull guide for Qwen/Qwen2.5-7B-InstructQwen/Qwen2.5-7B-Instruct speed on RTX 4090Qwen/Qwen2.5-7B-Instruct Q4 requirements