Nemotron-Cascade 14B
Nemotron-Cascade 14B is an open-weights language model from NVIDIA, released December 15, 2025. It has 14B parameters (dense).
Building general-purpose reasoning models with reinforcement learning (RL) entails substantial cross-domain heterogeneity, including large variation in inference-time response lengths and verification latency.
Check it against your own PC →
Can you run Nemotron-Cascade 14B locally?
The smallest common GPU it runs on is 6 GB of VRAM (with 32 GB of RAM): Q3_K_M, split GPU / CPU, roughly 6 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Runs, slowly | Q3_K_M (okay) | 5.2 GB | 4.8 GB | ~6 |
| 8 GB VRAM | Runs, slowly | Q4_K_M (very good) | 7.2 GB | 4.5 GB | ~6 |
| 12 GB VRAM | Runs on GPU | IQ4_XS (good) | 10.6 GB | – | ~28 |
| 16 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 14.7 GB | – | ~25 |
| 24 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 14.7 GB | – | ~47 |
| 32 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 14.7 GB | – | ~86 |
Benchmark results
Epoch AI has not published results for Nemotron-Cascade 14B yet. New models are usually evaluated within days to weeks.
Links
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