NVIDIA Tesla M40 - 24GB usable
Cheapest 24GB GPU at ~$80. Maxwell architecture is slow but the VRAM capacity is real. Needs aftermarket cooling.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | Tesla M40 |
| Usable VRAM | 24GB |
| Architecture | Maxwell |
| CUDA / Stream Processors | 3,072 |
| Memory Bandwidth | 288 GB/s |
| TDP | 250W |
| FP32 TFLOPS | 7 |
Current Offers
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Lowest tracked offers by retailer
UK · GBP · Weekly since Sep 2026 · Shipping may be extra
- eBay (no current offer)
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.
Weekly offers table
| Date | eBay |
|---|---|
| Oct 9, 2026 | £160.00 |
| Oct 2, 2026 | £160.00 |
| Sep 25, 2026 | £208.69 |
| Sep 18, 2026 | £172.30 |
| Sep 11, 2026 | £208.69 |
For AI / LLM Use
Solid choice for 30B models and comfortable 14B inference. Slower generation, usable but not snappy. 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?
- 30B Q4_K_M, 14B full precision, 70B Q2 (tight)
- 14B Q6_K, 30B Q3_K (tight)
- 14B Q4_K_M, 7B full precision
- 7B Q6_K, 14B Q3_K (tight)
- 7B Q4_K_M only
Estimated Performance
Generation: ~22 tokens/sec
Prefill: ~125 tokens/sec
Recommended Quantisations
- Q4_K_M recommended for 30B models
- Q6_K or Q8 for 14B and below
- Full precision for 7B
Pros & Cons
Pros
- 24GB usable VRAM: handles large models
Cons
- Low memory bandwidth: slower token generation
- Older Maxwell architecture: verify current CUDA support
- No display output: headless only
- May need aftermarket cooling solution
Community Verdict
- r/LocalLLaMA
The absolute cheapest 24GB card. Passive cooled so you need a blower mod. Slow but VRAM is VRAM.
Source