NVIDIA ships open-weight models as a software-and-services adjacency to the GPU business. The 2026 NVIDIA open-weight catalogue includes the Nemotron family (Nano, Mini, Super, Ultra variants), the Cosmos world foundation models for robotics, the Llama-Nemotron specialised finetune family, Eagle vision-language models, plus dozens of specialised models for synthetic data, agentic workflows, and ASR. This page consolidates the catalogue.
Key Findings
- Llama 3.1 Nemotron Ultra 253B is NVIDIA\u2019s flagship 2026 open-weight model, a 253B-parameter dense reasoning model derived from Llama 3.1 with strong AIME and GPQA scores.
- Llama 3.3 Nemotron Super 49B is NVIDIA\u2019s most-deployed mid-size open model with strong instruction following and tool use, competing directly with Qwen 32B and Llama 3.1 70B.
- NVIDIA Cosmos (released January 2025) is a family of world foundation models for robotics and autonomous systems, generating physically realistic video from text or image prompts plus reasoning over physical-world dynamics.
- Eagle 2 and Eagle 2.5 are NVIDIA\u2019s vision-language model families covering general VLM and document understanding workloads with open weights.
- The NV-Embed-v2 embedding model holds the top position on the MTEB v2 leaderboard among open-weight English embedders; combined with related Nemotron variants for data generation, NVIDIA has a complete open AI primitive stack.
NVIDIA Open-Weight Model Catalogue (May 2026)
| Family | Variant | Capability | License |
|---|---|---|---|
| Nemotron 4 / Nemotron 5 | 340B base / 15B / various | General-purpose | NVIDIA Open Model Licence |
| Llama 3.1 Nemotron Ultra 253B | ~253B | Reasoning, agentic | NVIDIA Open Model Licence + Llama 3.1 Community |
| Llama 3.3 Nemotron Super 49B | ~49B | General-purpose mid-size | NVIDIA Open Model Licence + Llama 3.3 Community |
| Llama 3.2 Nemotron Mini 4B | ~4B | Edge-deploy text | NVIDIA Open Model Licence + Llama 3.2 Community |
| Llama 3 Nemotron Nano 8B | ~8B | General-purpose small | NVIDIA Open Model Licence + Llama 3 Community |
| Cosmos Predict 1.0 (14B / 7B) | ~14B / ~7B | World model video generation | NVIDIA Open Model Licence |
| Cosmos Reason 1.0 | ~7B | Physical-world reasoning | NVIDIA Open Model Licence |
| Cosmos Transfer 1.0 | ~7B | Video-to-video transformation | NVIDIA Open Model Licence |
| Eagle 2 (varies) | ~varies | Vision-language | NVIDIA Open Model Licence |
| NV-Embed-v2 | ~7B | Embedding | CC-BY-NC |
| Canary 1B | ~1B | ASR English-focused | CC-BY-4.0 |
| Parakeet TDT 1.1B | ~1.1B | ASR streaming | CC-BY-4.0 |
| NVLM 1.0 72B | ~72B | Vision-language | CC-BY-NC + Research |
| Nemotron-CC pretraining dataset | ~6.3T tokens | Open pretraining data | Multi-licence (curated open) |
Cosmos Detail
| Cosmos Variant | Function |
|---|---|
| Cosmos Predict | Text or image to video; world-model future-state prediction |
| Cosmos Reason | Reasoning over physical-world inputs including video |
| Cosmos Transfer | Video-to-video transformation with control conditioning |
| Cosmos Tokenizer | Visual tokenisation for downstream training |
| Cosmos Curator | Data curation for robotics training |
Cosmos is positioned for robotics, autonomous vehicles, and embodied AI use cases where physically-realistic world simulation matters more than generic video aesthetic quality.
Strategic Context
Three patterns define NVIDIA\u2019s 2026 open-weight strategy. First, the GPU-platform tie-in: NVIDIA releases open models that are optimised for NVIDIA NIM microservices, TensorRT-LLM serving, and Triton Inference Server, creating a tight integration between model release and GPU consumption. Second, the specialised model catalogue: NVIDIA releases dozens of specialised models for ASR, embedding, reranking, synthetic data, and agent workflows rather than competing on frontier language model benchmarks. Third, the Cosmos world model bet: by releasing world foundation models open-weight, NVIDIA positions the robotics and physical AI ecosystem to compound on NVIDIA-platform tools.
Brand Visibility Implications
NVIDIA open-weight releases are a high-citation procurement category for AI infrastructure decisions. AI assistant queries about "NVIDIA Nemotron vs Llama", "Cosmos world model robotics", "NV-Embed-v2 vs OpenAI", and similar terms drive direct procurement decisions. Brands selling AI infrastructure, robotics AI, NIM-adjacent products, and NVIDIA partner services face strong AI-mediated discovery surface for this category.
Methodology
Model data compiled from NVIDIA Hugging Face disclosures and NVIDIA developer documentation through 23 May 2026. Updated quarterly.
How Presenc AI Helps
Presenc AI monitors brand visibility on NVIDIA Nemotron, Cosmos, and adjacent open-weight queries across ChatGPT, Claude, Gemini, and Perplexity. For AI infrastructure brands, robotics AI vendors, NIM-adjacent products, and NVIDIA partner services, the platform identifies the prompts driving procurement-research traffic and the gaps where new content unlocks share of voice.