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Nemotron is NVIDIA’s open-weight language model family, tuned for reasoning, tool use, and synthetic data generation. Variants span 4B to 340B parameters.
See all models from NVIDIAModels in family
8
Open weight
8
API only
0
Avg score
54.1
Top benchmark
87.0
GPQA
Total HF downloads
1.7M
Primary modality
Text
Context window
33K – 1.0M
First release
Apr 2026
Latest release
Oct 2026
Every release in the Nemotron family, ranked by composite score across benchmarks, popularity, efficiency, and versatility.
| # | Model | Modality | Score | Params | Released |
|---|---|---|---|---|---|
| 1 | audio | BB60.6 | 34B | Oct 2026 | |
| 2 | text | BB60.4 | 120B | Oct 2026 | |
| 3 | text | BB59.8 | 74B | Oct 2026 | |
| 4 | text | BB59.1 | 550B | Jun 2026 | |
| 5 | embedding | BB56.7 | 1.1B | Jul 2026 | |
| 6 | text | CC54.3 | 30B | Apr 2026 | |
| 7 | embedding | CC47.3 | 8B | Jul 2026 | |
| 8 | text | DD34.4 | 30B | Aug 2026 |
When a family spans multiple modalities, the strongest model in each one.
How the family splits across text, image, video, audio, embedding, and decision releases.
When each release shipped, newest first. Useful for tracking version cadence.
Oct 28
Aug 11
Jul 16
Jul 15
Jun 4
Apr 28
Composite grades across this family. Higher is better, blending benchmarks, popularity, and efficiency.
Models with downloadable weights, ranked by composite score.
| # | Model | Modality | Score | Params | Released |
|---|---|---|---|---|---|
| 1 | audio | BB60.6 | 34B | Oct 2026 | |
| 2 | text | BB60.4 | 120B | Oct 2026 | |
| 3 | text | BB59.8 | 74B | Oct 2026 | |
| 4 | text | BB59.1 | 550B | Jun 2026 | |
| 5 | embedding | BB56.7 | 1.1B | Jul 2026 | |
| 6 | text | CC54.3 | 30B | Apr 2026 | |
| 7 | embedding | CC47.3 | 8B | Jul 2026 | |
| 8 | text | DD34.4 | 30B | Aug 2026 |
The Nemotron family is a series of AI models from NVIDIA. This page lists every release in the family with its benchmark scores, parameter count, and hardware requirements.
By composite score, Nemotron 3.5 Transcribe is currently the top model in the family. For local inference, match the parameter count to your VRAM budget. For quality, pick the highest scorer that fits.
See the open-weight section above for models you can run locally. The API-only section lists closed releases that must be accessed through the provider’s API.
Spin up an instance in the cloud, or pick local hardware that fits.
Advertising disclosure: we earn commissions when you shop through the links below.
Vast.ai
Decentralized GPU marketplace with the lowest hourly prices.
RunPod
Pay-per-second GPU rentals starting at $0.20/hr.
Digital Ocean
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Vultr
GPU cloud with hourly and monthly plans, starting at $0.50/hr.
GPU Mart
Dedicated GPU servers and VPS billed monthly, starting at $0.50/hr.
PPQ.ai
Multi-model inference gateway for production workloads.
Find Local Hardware
See which GPU, Mac, or workstation can run Nemotron on-prem.
Local LLM Mini PCs
Compact machines that run Nemotron on your desk. Chosen for local inference.
Benchmark data sourced from: Hugging Face, Arena.ai, Artificial Analysis.
