SourceAWS Machine Learning Blog•Stalecollected in 5m
Nemotron 3 Super Launches on Bedrock
#generative-ai#cloud-inference#model-deploymentnvidia-nemotron-3-supernvidianemotron-3-superamazon-bedrock
💡NVIDIA's powerful Nemotron 3 Super on Bedrock: specs, use cases, quickstart guide.
⚡ 30-Second TL;DR
What Changed
NVIDIA Nemotron 3 Super now available via Amazon Bedrock
Why It Matters
Brings NVIDIA's advanced LLM to AWS users without self-hosting, speeding up GenAI prototyping and deployment on scalable Bedrock infrastructure.
What To Do Next
Log into Amazon Bedrock console and test Nemotron 3 Super model inference via the playground.
Who should care:Developers & AI Engineers
Key Points
- •NVIDIA Nemotron 3 Super now available via Amazon Bedrock
- •Details technical specs of the high-performance LLM
- •Outlines generative AI application use cases
- •Includes step-by-step setup guide for Bedrock users
🧠 Deep Insight
Background and context from public sources — not the original article. 8 sources cited.
🔑 Enhanced Key Takeaways
- •Nemotron 3 Super is a 12B active / 120B total parameter hybrid Mixture-of-Experts (MoE) model with Mamba-Transformer architecture optimized for multi-agent applications like reasoning and tool calling[1][2][3].
- •It achieves up to 2.2x higher inference throughput than GPT-OSS-120B and 7.5x higher than Qwen3.5-122B on 8k input/16k output benchmarks, while supporting up to 1M token context length[2][7].
- •The model incorporates novel technologies including LatentMoE for accuracy, MTP layers for speculative decoding, and NVFP4 pretraining for 4x faster inference on NVIDIA B200 GPUs[2][5][6].
- •Fully open-source with weights, data, and recipes available, accessible via Hugging Face, NVIDIA NGC, NIM, and hosted platforms like Together AI[3][4].
📊 Competitor Analysis▸ Show
| Feature | Nemotron 3 Super | GPT-OSS-120B | Qwen3.5-122B |
|---|---|---|---|
| Parameters | 120B total (12B active MoE) | 120B | 122B |
| Architecture | Hybrid Mamba-Transformer MoE | Transformer | MoE |
| Throughput (8k in/16k out) | Baseline | 2.2x slower | 7.5x slower |
| Context Length | 1M tokens | <1M (outperforms on RULER) | <1M (outperforms on RULER) |
| Benchmarks | Leading on GPQA Diamond, AIME 2025, LiveCodeBench | Comparable/lower | Comparable/lower |
🛠️ Technical Deep Dive
- Architecture: Hybrid Mixture-of-Experts (MoE) with Mamba-Transformer backbone; 120B total parameters, 12B activated per forward pass via sparse MoE routing; includes LatentMoE (hardware-aware experts), MTP (Multi-Token Prediction) layers for speculative decoding[2][3][5][7].
- Pretraining: NVFP4 format on 25-trillion-token corpus; optimized for NVIDIA Blackwell GPUs, 4x inference speedup on B200 vs FP8 on H100[2][6][7].
- Inference Configs: Max model length 65,536 tokens; tensor parallel size 2-4; 90% GPU memory utilization; KV cache auto/FP8; FLASH_ATTN backend; vLLM or TRT-LLM serving on 8x B200-SXM[1][7].
- Memory Estimates: FP16 ~240GB VRAM; 4-bit quantized ~60-80GB (multi-GPU/A100/H100 required); supports QLoRA fine-tuning via NVIDIA NeMo[4].
🔮 Future ImplicationsAI analysis grounded in cited sources
Nemotron 3 Super enables single-GPU multi-agent deployments
Its MoE design with 12B active parameters and high throughput optimizes for running multiple collaborating agents on one GPU, reducing costs for agentic applications[3].
NVFP4 pretraining sets standard for Blackwell efficiency
Native NVFP4 cuts memory and speeds inference 4x on B200 GPUs versus prior formats, accelerating adoption of next-gen NVIDIA hardware[6].
Open-source release boosts enterprise customization
Full openness of weights, data, and recipes via Hugging Face/NGC allows fine-tuning with QLoRA for domain-specific tasks on A100/H100 clusters[4].
⏳ Timeline
2025-12
Nemotron 3 Nano released as first in Nemotron 3 series with hybrid MoE architecture
2026-03
Nemotron 3 Super released: 120B MoE model with LatentMoE, MTP, NVFP4 for agentic reasoning
2026-03
Nemotron 3 Super launched on Amazon Bedrock for generative AI use cases
📎 Sources (8)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
- artificialanalysis.ai — Nvidia Nemotron 3 Super the New Leader in Open Efficient Intelligence
- research.nvidia.com — Nemotron 3 Super
- together.ai — Nvidia Nemotron 3 Super
- mindstudio.ai — What Is Nvidia Neotron 3 Super
- research.nvidia.com — Nemotron 3
- developer.nvidia.com — Introducing Nemotron 3 Super an Open Hybrid Mamba Transformer Moe for Agentic Reasoning
- research.nvidia.com — Nvidia Nemotron 3 Super Technical Report
- aiagentsdirectory.com — Nvidia Nemotron 3 Super Everything You Need to Know
📰
Weekly AI Recap
Read this week's curated digest of top AI events →
👉Related Updates
AI-curated news aggregator. All content rights belong to original publishers.
Original source: AWS Machine Learning Blog ↗
This is a summary, not the original. Read the source, or get the weekly briefing.
The weekly digest
One email a week. Unsubscribe anytime.