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 A100 80GB SXM4 run Qwen/Qwen3-Coder-Next?

Runs Q480GB VRAM availableRequires 45GB+

NVIDIA A100 80GB SXM4 meets the minimum VRAM requirement for Q4 inference of Qwen/Qwen3-Coder-Next. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

NVIDIA A100 80GB SXM4 can run Qwen/Qwen3-Coder-Next with Q4 quantization. At approximately 62 tokens/second, you can expect Good speed - acceptable for interactive use.

You have 35GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q445GB80GB62.43 tok/s✅ Fits comfortably
Q890GB80GB44.12 tok/s❌ Not recommended
FP16179GB80GB23.86 tok/s❌ Not recommended

Suitable alternatives

AMD Instinct MI300X
192GB
140.03 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
124.22 tok/s
Price: —
AMD Instinct MI300X
192GB
117.30 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
103.46 tok/s
Price: —
AMD Instinct MI250X
128GB
96.52 tok/s
Price: —

More questions

NVIDIA A100 80GB SXM4 specs & pricingFull guide for Qwen/Qwen3-Coder-NextQwen/Qwen3-Coder-Next speed on NVIDIA A100 80GB SXM4Qwen/Qwen3-Coder-Next Q4 requirements