NVIDIA Tesla K80 - 12GB usable
Avoid for modern local AI: its advertised 24GB is split across two independent 12GB GPUs.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | Tesla K80 |
| Usable VRAM | 12GB (24GB split across the board) |
| Architecture | Kepler |
| CUDA / Stream Processors | 4,992 |
| Memory Bandwidth | 480 GB/s |
| TDP | 300W |
| FP32 TFLOPS | 8.7 |
Current Offers
Prices last updated:
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Lowest tracked offers by retailer
US · USD · Weekly since May 2026 · Shipping may be extra
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
| Date | eBay | Amazon | Newegg |
|---|---|---|---|
| Today, Nov 3, 2026 | $54.99 | $178.02 | – |
| Oct 30, 2026 | $54.99 | – | – |
| Oct 23, 2026 | $54.99 | – | – |
| Oct 9, 2026 | $54.99 | – | $99.99 |
| Oct 2, 2026 | $54.99 | – | $224.00 |
| Sep 25, 2026 | $54.99 | – | $224.00 |
| Sep 18, 2026 | $54.99 | – | $224.00 |
| Sep 11, 2026 | $54.99 | – | $224.00 |
| Sep 4, 2026 | $59.99 | – | $224.00 |
| Sep 1, 2026 | $59.99 | – | $224.00 |
| Aug 28, 2026 | $54.99 | – | $224.00 |
| Aug 21, 2026 | $54.99 | – | $224.00 |
| Aug 14, 2026 | $59.99 | – | $224.00 |
| Aug 7, 2026 | $59.99 | – | $99.99 |
| Jul 31, 2026 | $59.99 | – | $224.00 |
| Jul 24, 2026 | $57.50 | – | $99.99 |
| Jul 17, 2026 | $59.99 | – | $99.99 |
| Jul 10, 2026 | $59.99 | – | $99.99 |
| Jul 3, 2026 | $59.99 | – | $99.99 |
| Jun 26, 2026 | $59.99 | – | $99.99 |
| Jun 19, 2026 | $59.99 | – | $99.99 |
| Jun 12, 2026 | $59.99 | – | $99.99 |
| Jun 5, 2026 | $59.99 | – | $99.99 |
| May 29, 2026 | $59.99 | – | $99.99 |
| May 22, 2026 | $59.99 | – | $99.99 |
| May 15, 2026 | $54.99 | – | $99.99 |
| May 8, 2026 | $59.95 | – | $99.99 |
For AI / LLM Use
Entry-level for local AI. Handles 7B-8B models well. Older architecture may have limited software support (check CUDA compatibility). Datacenter card with no display output, may need aftermarket cooling.
What Models Can It Run?
- 14B Q4_K_M, 7B full precision
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~36 tokens/sec
Prefill: ~155 tokens/sec
Recommended Quantisations
- Q4_K_M for 14B (tight fit)
- Q6_K or Q8 for 7B models
Pros & Cons
Pros
- Very low acquisition cost
Cons
- 12GB usable VRAM: may need quantization for 30B+ models
- 24GB is split across multiple GPUs; one model sees 12GB per GPU
- Moderate memory bandwidth: not the fastest for inference
- 300W TDP: high power draw
- Older Kepler architecture: verify current CUDA support
- No display output: headless only
- May need aftermarket cooling solution
- Only 12GB is usable by one model without explicit sharding
- Kepler software support is obsolete for many current stacks
- Dual-GPU 300W board with substantial cooling requirements
Community Verdict
- r/LocalLLaMA
Avoid. Dual-GPU means 12GB per die, Kepler lacks modern CUDA support, and it draws 300W. Buy a P40 instead.
Source