vs
1:1
overall capability wins (1 ties across 3 scored). Nemotron Nano 3 30B leads overall.
- Pricing0:3
- Specs1:1
Verdict
Nemotron Nano 3 30B allows ~4.0x more max output (66K vs 16K); Nemotron Nano 3 30B is ~2.3x cheaper on a blended token basis than Nemotron Super 3 120B.
- Nemotron Nano 3 30B allows ~4.0x more max output (66K vs 16K)
- Nemotron Nano 3 30B is ~2.3x cheaper on a blended token basis than Nemotron Super 3 120B
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Nemotron Super 3 120B
- $0.23
- Nemotron Nano 3 30B
- $0.10
Nemotron Nano 3 30B is about 2.3x cheaper on this workload.
Price per 1M tokens
Full comparison
Organization
NVIDIA
NVIDIA
Family
Nemotron
Nemotron
License
NVIDIA Open Model
NVIDIA Open Model
Open weights
Yes
Yes
Release
Mar 11, 2026
Dec 15, 2025
Knowledge cutoff
-
-
API / provider
NVIDIA NIM
NVIDIA NIM
Modalities
text → text
text → text
Specs
Context window
262K
262K
Max output
16K
66K
Parameters
120B (12B act.)
30B (3.5B act.)
Pricing
Input $/1M
$0.10
$0.05
Output $/1M
$0.50
$0.20
Blended $/1M (3∶1)
$0.20
$0.09
Speed
tok/s
68
68
TTFT (s)
0.4
0.4
Reasoning
MMLU-Pro
—
78.3
GPQA Diamond
—
—
Humanity's Last Exam
—
10.6
AIME 2025
—
89.1
MATH-500
—
—
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
—
—
AA-LCR v1.1
—
—
CritPt
—
—
MMMU-Pro
—
—
IFBench
—
—
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
—
SWE-bench Pro
—
—
SWE-bench Multilingual
—
—
LiveCodeBench
—
68.3
Terminal-Bench 2.1
—
—
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
—
—
CursorBench
—
—
SWE-Rebench
—
—
NL2Repo-Bench
—
—
DeepSWE
—
—
WebDev Arena
—
—
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
—
—
| Metric | Nemotron Super 3 120B | Nemotron Nano 3 30B | Delta |
|---|---|---|---|
| Identity | |||
| Organization | NVIDIA | NVIDIA | — |
| Family | Nemotron | Nemotron | — |
| License | NVIDIA Open Model | NVIDIA Open Model | — |
| Open weights | Yes | Yes | — |
| Release | Mar 11, 2026 | Dec 15, 2025 | — |
| Knowledge cutoff | - | - | — |
| API / provider | NVIDIA NIM | NVIDIA NIM | — |
| Modalities | text → text | text → text | — |
| Specs | |||
| Context window | 262K | 262K | tie |
| Max output | 16K | 66K | B +49K |
| Parameters | 120B (12B act.) | 30B (3.5B act.) | A +90 |
| Pricing | |||
| Input $/1M | $0.10 | $0.05 | B +$0.05 |
| Output $/1M | $0.50 | $0.20 | B +$0.30 |
| Blended $/1M (3∶1) | $0.20 | $0.09 | B +$0.11 |
| Speed | |||
| tok/s | 68 | 68 | tie |
| TTFT (s) | 0.4 | 0.4 | tie |
| Reasoning | |||
| MMLU-Pro | — | 78.3 | — |
| GPQA Diamond | — | — | — |
| Humanity's Last Exam | — | 10.6 | — |
| AIME 2025 | — | 89.1 | — |
| MATH-500 | — | — | — |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | — | — | — |
| AA-LCR v1.1 | — | — | — |
| CritPt | — | — | — |
| MMMU-Pro | — | — | — |
| IFBench | — | — | — |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | — | — |
| SWE-bench Pro | — | — | — |
| SWE-bench Multilingual | — | — | — |
| LiveCodeBench | — | 68.3 | — |
| Terminal-Bench 2.1 | — | — | — |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | — | — | — |
| CursorBench | — | — | — |
| SWE-Rebench | — | — | — |
| NL2Repo-Bench | — | — | — |
| DeepSWE | — | — | — |
| WebDev Arena | — | — | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | — | — | — |
Nemotron Super 3 120B
- Context
- 262K / 16K out
- Parameters
- 120B (12B act.)
- Price
- $0.10 / $0.50
- Speed
- 68 tok/s · 0.4s TTFT
- Modalities
- text → text
- License
- NVIDIA Open Model
Hybrid Mamba-MoE Nemotron 3 mid-tier — 120B total / 12B active with reasoning budgets for agentic NIM deployments.
Nemotron Nano 3 30B
- Context
- 262K / 66K out
- Parameters
- 30B (3.5B act.)
- Price
- $0.05 / $0.20
- Speed
- 68 tok/s · 0.4s TTFT
- Modalities
- text → text
- License
- NVIDIA Open Model
Efficient Nemotron Nano 3 MoE — Mamba-2 + attention hybrid with 3.5B active params and 262K context on NIM.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.
These two models have no overlapping published benchmarks in our dataset. Compare specs and pricing instead.