Nemotron 3 Nano 30B needs ~24.3 GB VRAM. NVIDIA L4 24GB has 24.0 GB. With Q4_K_M quantization, expect ~8 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
0.3 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~0.3 GB host RAM)
Decode
8.3 tok/s
TTFT
23215 ms
Safe context
14K
Memory
24.3 GB / 24.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload | 11.5 tok/s | 9219 ms | 14K |
| Coding | S | Runs with offload (needs ~0.3 GB host RAM) | 8.3 tok/s | 23215 ms | 14K |
| Agentic Coding | A | Very compromised (needs ~1.9 GB host RAM) | 6.8 tok/s | 41293 ms | 14K |
| Reasoning | S | Runs with offload (needs ~0.3 GB host RAM) | 8.3 tok/s | 27436 ms | 14K |
| RAG | A | Very compromised (needs ~1.9 GB host RAM) | 6.8 tok/s |
How Nemotron 3 Nano 30B (30B params) fits at each quantization level on NVIDIA L4 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | S90 |
Q3_K_S | 3 | 14.7 GB | Low | S90 |
NVFP4 | 4 |
Copy-paste commands to run Nemotron 3 Nano 30B on your machine.
Run
ollama run nemotron-nano:30bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 29.5 tok/s | ||
| 35B | A | 17.7 tok/s |
Yes, NVIDIA L4 24GB can run Nemotron 3 Nano 30B with a S grade (Runs with offload (needs ~0.3 GB host RAM)). Expected decode speed: 8.3 tok/s.
Nemotron 3 Nano 30B (30B parameters) requires approximately 24.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Nemotron 3 Nano 30B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA L4 24GB, Nemotron 3 Nano 30B achieves approximately 8.3 tokens per second decode speed with a time-to-first-token of 23215ms using Q4_K_M quantization.
For coding workloads, Nemotron 3 Nano 30B on NVIDIA L4 24GB receives a S grade with 8.3 tok/s and 14K context.
On NVIDIA L4 24GB, Nemotron 3 Nano 30B can safely use up to 14K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/nemotron-3-nano-30b-on-l4-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 51616 ms |
| 14K |
16.8 GB |
| Medium |
| S90 |
Q4_K_MBest for your GPU | 4 | 18.3 GB | Medium | S89 |
Q5_K_M | 5 | 21.6 GB | High | F0 |
Q6_K | 6 | 24.6 GB | High | F0 |
Q8_0 | 8 | 32.1 GB | Very High | F0 |
F16 | 16 | 61.5 GB | Maximum | F0 |
| 32B | A | 6.3 tok/s |
| 30.5B | S | 29.5 tok/s |
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.