NVIDIA RTX 3080 - 10GB usable

Popular but 10GB VRAM is tight. Fine for 7B models, struggles beyond that.

Specifications

BrandNVIDIA
ModelRTX 3080
Usable VRAM10GB
ArchitectureAmpere
CUDA / Stream Processors8,704
Memory Bandwidth760 GB/s
TDP320W
FP32 TFLOPS30

Current Offers

Used from $400New from $469

Prices last updated:

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Lowest tracked offers by retailer

US · USD · Weekly since Aug 2026 · Shipping may be extra

  • eBay $400 near 90-day high
  • Amazon $469 current
  • Newegg (no current offer)
$250$500$750$1,000Aug 7Aug 29Sep 20Oct 12Nov 3Newegg $785Amazon $469eBay $400
About these prices

Each line is the lowest offer we tracked from that retailer at weekly snapshots, ending at today's offer. The condition can vary between snapshots (new, used, or unrecorded for older ones). eBay prices exclude shipping. Tax is excluded. Amazon shows a current price only.

Weekly offers table
Lowest tracked offer per retailer · US · USD
DateeBayAmazonNewegg
Today, Nov 3, 2026 $399.99$469.00–
Oct 30, 2026 $410.00––
Oct 23, 2026 $399.00––
Oct 9, 2026 $364.99––
Oct 2, 2026 $350.00–$785.00
Sep 25, 2026 $290.00–$845.00
Sep 18, 2026 $335.00–$785.00
Sep 11, 2026 $349.99–$449.99
Sep 4, 2026 ––$706.56
Sep 1, 2026 ––$785.00
Aug 28, 2026 ––$785.00
Aug 21, 2026 ––$580.00
Aug 14, 2026 ––$785.00
Aug 7, 2026 ––$706.56

For AI / LLM Use

Limited VRAM restricts you to 7B quantized models.

What Models Can It Run?

  • 7B Q6_K, 14B Q3_K (tight)
  • 7B Q4_K_M only

Estimated Performance

Generation: ~57 tokens/sec

Prefill: ~536 tokens/sec

Recommended Quantisations

  • Q4_K_M for 7B models
  • Q3_K for larger experiments

Pros & Cons

Pros

  • Ampere architecture: broad CUDA software support
  • Consumer card: easy to install, display output

Cons

  • Moderate memory bandwidth: not the fastest for inference
  • 320W TDP: high power draw

Community Verdict

  • r/LocalLLaMA

    10GB is tight for AI. Can run 7B models but you will hit VRAM limits quickly with larger models.

    Source