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 Alibaba-NLP/gte-Qwen2-1.5B-instruct?

Runs Q424GB VRAM availableRequires 3GB+

RX 7900 XTX meets the minimum VRAM requirement for Q4 inference of Alibaba-NLP/gte-Qwen2-1.5B-instruct. 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 Alibaba-NLP/gte-Qwen2-1.5B-instruct with Q4 quantization. At approximately 157 tokens/second, you can expect Excellent speed - conversational response times under 1 second.

You have 21GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q43GB24GB157.03 tok/s✅ Fits comfortably
Q85GB24GB97.88 tok/s✅ Fits comfortably
FP1611GB24GB54.35 tok/s✅ Fits comfortably

Best current price

RX 7900 XTX
$899.00 on Amazon
Check Price

Suitable alternatives

AMD Instinct MI300X
192GB
829.94 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
664.84 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
525.33 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
522.69 tok/s
Price: —
AMD Instinct MI300X
192GB
484.94 tok/s
Price: —

More questions

RX 7900 XTX specs & pricingFull guide for Alibaba-NLP/gte-Qwen2-1.5B-instructAlibaba-NLP/gte-Qwen2-1.5B-instruct speed on RX 7900 XTXAlibaba-NLP/gte-Qwen2-1.5B-instruct Q4 requirements