NVIDIA
Updated May 2026
Nemotron
The GPU maker's own AI models, tuned for its hardware
NVIDIA doesn't just sell the hardware that every AI lab trains on — it also ships its own models, open-weight and optimized for NIM (NVIDIA Inference Microservices). Nemotron models start from community base models (Llama, Mistral) and apply NVIDIA's neural architecture search and post-training recipes. They're aimed at enterprises running on DGX or NVIDIA AI Enterprise licenses.
Variants
4
Best at
open weights + NVIDIA optimization
Max context
128K
tokens
Pricing
NIM (build.nvidia.com)
$0
per free prototyping tier
NVIDIA AI Enterprise
~$4500
per GPU/year for production
Self-host
$0
per download from HuggingFace
Variants
Sort the table by context window or cost to find the right variant. Click any version below for a battle card with ranks, pricing notes, and official links.
| Modalities | ||||
|---|---|---|---|---|
Nemotron 3 Ultra nemotron-3-ultra | 128K | varies / varies | 2026 | textvisioncode |
Nemotron 3 Super nemotron-3-super | 128K | varies / varies | 2026 | textvision |
Llama Nemotron Ultra 253B llama-3-1-nemotron-ultra-253b-v1 | 128K | varies / varies | 2025 | text |
NIM Microservices nvidia-nim | — | varies / varies | 2024 | textvisioncodeaudioimagevideo |
Battle card
Context rank
#1
within Nemotron
Capability rank
#2
modalities + reasoning
Weights
Open
self-hostable if licensed
Best fights to pick
- enterprise reasoning workloads
- multi-step agent pipelines
- on-prem NVIDIA deployments
Rankings are Tendril directory ranks, computed from the model data shown here. Public benchmark leaderboards change often, so official docs and current benchmark pages should be checked before buying or deploying.
Learn
Lessons about this model
Structured lessons that cover Nemotron directly or put it in context alongside its rivals.
Check yourself
Quizzes
Short, mixed-difficulty quiz sets on Nemotron and its model family.
Open-Weight Families: Llama, Mistral, Qwen, DeepSeek, Gemma
7 questions
The open ecosystem that shook the industry.
Start quiz →Hands-on
Try these prompts
Ready-made prompts that show Nemotron at its best. Use them in your own AI workspace, then compare the output with what you learned in Tendril.
Nemotron for instruction-tuning a base model
CreatorsNVIDIA's Nemotron family is positioned as strong base+instruct weights you can run on their hardware.
You are an assistant specialized in clinical note triage. Classify this note into one of: URGENT, ROUTINE, INFORMATIONAL. Explain your reasoning in 2 sentences. [Clinical note]
Run a Nemotron on a DGX cloud instance
CreatorsDemonstrate how the NVIDIA stack (NIM + Nemotron) feels end-to-end.
curl -X POST https://integrate.api.nvidia.com/v1/chat/completions \
-H 'Authorization: Bearer $NVIDIA_API_KEY' \
-d '{"model":"nvidia/llama-3.1-nemotron-70b-instruct","messages":[{"role":"user","content":"Summarize the plot of Hamlet in a haiku."}]}'Compare Nemotron to base Llama
BuildersNemotron usually beats the underlying Llama on RewardBench — verify on a judgment task.
Which of these two answers better addresses the user's question? Explain your judgment. Question: 'How do I politely decline a meeting?' A: 'Just say no.' B: 'Thanks for the invite — I don't have the bandwidth this week, but I'd love to see notes or help async.'
Print & keep
Printable reference
One-page summaries and flowcharts — great for desks, classrooms, or study sessions.
Go deeper
Official resources
Straight from the lab — docs, API references, and the chat surfaces you can try today.
Strengths
- open weights + NVIDIA optimization
- NIM platform is a great free playground
- designed for enterprise DGX/H100 clusters
Limits
- benchmarks trail the frontier labs
- best performance assumes NVIDIA hardware
- less known to general users