NVIDIA RTX 4090 — 24GB
Fastest consumer GPU for AI inference. Worth it if speed matters more than value.
Specifications
| Brand | NVIDIA |
|---|---|
| Model | RTX 4090 |
| VRAM | 24GB |
| Architecture | Ada |
| CUDA / Stream Processors | 16,384 |
| Memory Bandwidth | 1008 GB/s |
| TDP | 450W |
| FP32 TFLOPS | 83 |
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For AI / LLM Use
Solid choice for 30B models and comfortable 14B inference.
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: ~76 tokens/sec
Prefill: ~1482 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 VRAM — handles large models
- High memory bandwidth for fast generation
- Ada architecture — good software support
- Consumer card — easy to install, display output
Cons
- 450W TDP — high power draw
Community Verdict
Average score: 9.5/10 (1 review)