Nemotron 3 Nano 30B needs ~24.3 GB VRAM. RTX 3090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~26 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
28.0 tok/s
TTFT
6909 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 | 38.5 tok/s | 2744 ms | 14K |
| Coding | S | Runs with offload | 26.1 tok/s | 7427 ms | 14K |
| Agentic Coding | A | Very compromised (needs ~1.9 GB host RAM) | 22.9 tok/s | 12289 ms | 14K |
| Reasoning | S | Runs with offload (needs ~0.3 GB host RAM) | 28.0 tok/s | 8165 ms | 14K |
| RAG | A | Very compromised (needs ~1.9 GB host RAM) | 22.9 tok/s | 15362 ms |
How Nemotron 3 Nano 30B (30B params) fits at each quantization level on RTX 3090 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 | 99.1 tok/s | ||
| 35B | A | 55.5 tok/s |
Yes, RTX 3090 24GB can run Nemotron 3 Nano 30B with a S grade (Runs with offload). Expected decode speed: 26.1 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 RTX 3090 24GB, Nemotron 3 Nano 30B achieves approximately 26.1 tokens per second decode speed with a time-to-first-token of 7427ms using Q4_K_M quantization.
For coding workloads, Nemotron 3 Nano 30B on RTX 3090 24GB receives a S grade with 26.1 tok/s and 14K context.
On RTX 3090 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-rtx-3090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 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 | 21.3 tok/s |
| 30.5B | S | 99.1 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.