Consumer AI GPUs
Consumer AI GPUs are the most commonly used AI hardware by individual developers and creators. They offer excellent price-performance for Stable Diffusion, local LLMs, and LoRA fine-tuning.
Mainstream Consumer AI GPU Comparison
| Model | Memory | FP8 Compute | TDP | Price | Best For |
|---|---|---|---|---|---|
| NVIDIA RTX 4090 | 24GB GDDR6X | 2,642 TFLOPS | 450W | $1,599+ | LLM 70B (4-bit), SD XL |
| NVIDIA RTX 4080 SUPER | 16GB GDDR6X | N/A | 320W | $999 | SD XL, LLM 13B |
| NVIDIA RTX 4070 Ti SUPER | 16GB GDDR6X | N/A | 285W | $799 | SD 1.5, LLM 7B |
| NVIDIA RTX 4060 Ti 16GB | 16GB GDDR6 | N/A | 160W | $399 | Entry AI |
| NVIDIA RTX 3090 | 24GB GDDR6X | N/A | 350W | Used | Value (discontinued) |
Key Considerations
- 24GB memory threshold: Local LLM inference requires significant VRAM (>12GB)
- Missing data center features: No ECC, no MIG, no vGPU
- Driver limitations: GeForce driver vs NVIDIA RTX Enterprise
Selection Guide
By Budget
- $1,500+: RTX 4090 (24GB)
- $1,000: RTX 4080 SUPER (16GB)
- $800: RTX 4070 Ti SUPER (16GB)
- $400: RTX 4060 Ti 16GB
By Workload
- Local 70B LLM (4-bit quantization): RTX 4090 (24GB)
- Local 13B LLM: RTX 4080 SUPER (16GB)
- Stable Diffusion XL: RTX 4070 Ti SUPER (16GB)
- Stable Diffusion 1.5: RTX 4060 Ti 8GB and up
Important Notes
- Power requirements: RTX 4090 needs 850W+ PSU
- Physical dimensions: RTX 4090 is triple-slot thick
- Driver lock: Consumer drivers have AI training restrictions (use NVIDIA Studio driver)
- VRAM shortage: 70B models need CPU offload or model quantization
Detailed Product Pages
- NVIDIA RTX 4090 - Consumer flagship
- NVIDIA RTX 6000 Ada - Workstation edition (48GB)
- NVIDIA L40S - Data center edition
- Apple M-Series - Apple Silicon local LLM