Essentialai Rnj 1 speed on RTX 4070 Ti and quantization-level VRAM fit.
RTX 4070 Ti meets the minimum VRAM requirement for Q4 inference of Essentialai Rnj 1. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4070 Ti can run Essentialai Rnj 1 with Q4 quantization. At approximately 66 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 7GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 5GB | 12GB | 66.45 tok/s | ✅ Fits comfortably |
| Q8 | 9GB | 12GB | 46.51 tok/s | ✅ Fits comfortably |
| FP16 | 17GB | 12GB | 25.25 tok/s | ❌ Not recommended |
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RTX 4070 Ti can run Essentialai Rnj 1 at Q4 with an estimated 66 tok/s.
Q4 inference is estimated to need about 5GB VRAM on this page, while RTX 4070 Ti has 12GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.