Nemotron 3 Labs Ultra Math RL — Hardware Requirements & GPU Compatibility
ChatMath
Nemotron 3 Labs Ultra Math RL is a 560.5B-parameter open language model from NVIDIA in the Nemotron family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 336.84 GB of VRAM — see which GPUs and Macs can run it below.
Nemotron 3 Labs Ultra Math RL runs on a 512 GB+ Mac or a multi-GPU server
Best local pick → Mac Studio (M3 Ultra, 512GB) · Q4_K_M · 336.8 GB · ~12 tok/s
Macs from 256 GB (Q2_K · ~16 tok/s)
Other
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Nemotron 3 Labs Ultra Math RL
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve nvidia/Nemotron-3-Labs-Ultra-Math-RL --max-model-len 16384 --tensor-parallel-size 8Size the nodes from the table above
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Rent 5× H100 SXM · Q4_K_M
- Estimated hourly price
- ~$13.45/hr
- est., whole server
- GPUs
- 5 GPUs
- 400 GB of VRAM
How Much VRAM Does Nemotron 3 Labs Ultra Math RL Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 238.8 GB | 239 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Runs on Instinct MI325X 256 GB | |
| 273.8 GB | 274 GB | 3-bit medium — 3-bit medium quantization | Runs on Instinct MI350X 288 GB | |
| 336.8 GB | 337.1 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Runs on 5× H100 SXM 80 GB | |
| 399.9 GB | 400.1 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Runs on 6× H100 SXM 80 GB | |
| 463.0 GB | 463.2 GB | 6-bit, very good — 6-bit quantization, very good quality | Runs on 7× H100 SXM 80 GB | |
| 561.0 GB | 561.3 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Runs on 8× H100 SXM 80 GB | |
| 1121.6 GB | 1121.8 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Runs on 7× B200 192 GB |
Selected Q4_K_M
4-bit medium quantization336.8GBat 16K context
- Weights
- 336.3 GB
- KV cache
- 0.2 GB
- Overhead
- 0.3 GB
Server-class: ~336.8 GB at 16K context · about 5× H100 SXM 80 GB
Which Hardware Can Run Nemotron 3 Labs Ultra Math RL?
Q4_K_M · 336.8 GBNemotron 3 Labs Ultra Math RL (Q4_K_M) requires 336.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 438+ GB is recommended. Using the full 262K context window can add up to 3.3 GB, bringing total usage to 340.1 GB. No consumer GPU has enough memory. 1 device with unified memory can run Nemotron 3 Labs Ultra Math RL, including Mac Studio (M3 Ultra, 512GB).
Needs server-class hardware
Nemotron 3 Labs Ultra Math RL runs on a 512 GB+ Mac or a multi-GPU server · Q4_K_M needs ~336.8 GB
| Hardware | Quant | Memory | Speed | Context | Hardware page | |
|---|---|---|---|---|---|---|
| Mac 256 GB · Mac Studio (M3 Ultra, 256GB) | Q2_K | 238.7 GB | ~16 tok/s | 256K ctx | Mac Studio → | Q2_K · 238.7 GB · ~16 tok/s · 256K ctx |
| Mac 512 GB · Mac Studio (M3 Ultra, 512GB) | Q4_K_M | 336.8 GB | ~12 tok/s | 256K ctx | Mac Studio → | Q4_K_M · 336.8 GB · ~12 tok/s · 256K ctx |
| 5× H100 SXM 80 GB · 400 GB | Q4_K_M | 336.8 GB | — | 256K ctx | H100 SXM → | Q4_K_M · 336.8 GB · 256K ctx |
| 3× H200 SXM 141 GB · 423 GB | Q4_K_M | 336.8 GB | — | 256K ctx | H200 SXM → | Q4_K_M · 336.8 GB · 256K ctx |
| 2× B200 192 GB · 384 GB | Q4_K_M | 336.8 GB | — | 256K ctx | B200 → | Q4_K_M · 336.8 GB · 256K ctx |
Also: Mac Studio (M3 Ultra, 512GB) · NVIDIA DGX A100 640GB · NVIDIA DGX H100
By VRAM tier · typical GPUs and Macs at Q4_K_M
Consumer GPUs (up to 32 GB) and Macs up to 192 GB: too small for this model (needs ≥ 238.7 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Alternatives to Nemotron 3 Labs Ultra Math RL
Nemotron family · 42 models →Similar models
2| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Ling 3.1 FlashInclusion AI | — | 344.9 GB | —needs > 24 GB | same size |
| LongCat Flash ChatMeituan | — | 1244.5 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 560.5B
- Active parameters
- 57B per token
- Architecture
- NemotronHForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 131,072
- Release Date
- 2026-09-02
- License
- Other
Frequently Asked Questions
How much VRAM does Nemotron 3 Labs Ultra Math RL need?
Nemotron 3 Labs Ultra Math RL requires 336.8 GB of VRAM at Q4_K_M, or 1121.6 GB at BF16. Full 262K context adds up to 3.3 GB (340.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 560.5B × 4.8 bits ÷ 8 = 336.3 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 3.8 GB (at full 262K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run Nemotron 3 Labs Ultra Math RL?
No — Nemotron 3 Labs Ultra Math RL requires at least 238.8 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
What's the best quantization for Nemotron 3 Labs Ultra Math RL?
For Nemotron 3 Labs Ultra Math RL, Q4_K_M (336.8 GB) offers the best balance of quality and VRAM usage. Q5_K_M (399.9 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 238.8 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Nemotron 3 Labs Ultra Math RL on a Mac?
Yes — Mac Studio (M3 Ultra, 256GB) and 1 other Mac can run Nemotron 3 Labs Ultra Math RL, the smallest at Q2_K. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 336.8 GB of usable unified memory (RAM minus macOS overhead), from Mac Studio (M3 Ultra, 512GB).
Can I run Nemotron 3 Labs Ultra Math RL locally?
Yes — Nemotron 3 Labs Ultra Math RL can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
What's the download size of Nemotron 3 Labs Ultra Math RL?
At Q4_K_M, the download is about 336.31 GB. The full-precision BF16 version is 1121.05 GB. The smallest option (Q2_K) is 238.22 GB.
Which GPUs can run Nemotron 3 Labs Ultra Math RL?
No single consumer GPU has enough VRAM to run Nemotron 3 Labs Ultra Math RL at Q4_K_M (336.8 GB). Multi-GPU or professional hardware is required.
Which devices can run Nemotron 3 Labs Ultra Math RL?
1 device with unified memory can run Nemotron 3 Labs Ultra Math RL at Q4_K_M (336.8 GB), including Mac Studio (M3 Ultra, 512GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.