NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 vs NVIDIA: Nemotron 3 Super
Side-by-side comparison. Updated 2026-07-01.
Summary
Compare NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 and NVIDIA: Nemotron 3 Super across pricing, context window, modalities, strengths, weaknesses, and best-fit workloads.
Use the details below to weigh cost, context, modalities, and workload fit.
NVIDIA: Llama 3.3 Nemotron Super 49B V1.5
by Nvidia
Input pricing
$0.40
/1M input tokens
At a Glance
| Attribute | NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 | NVIDIA: Nemotron 3 Super |
|---|---|---|
| Provider | Nvidia | Nvidia |
| Tags | Agentic Intelligent | Intelligent Agentic Open Weight Long Context |
| Context | 131,072 tokens | 1,000,000 tokens |
| Input price | $0.40/1M | $0.09/1M |
| Output price | $0.40/1M | $0.45/1M |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
NVIDIA: Llama 3.3 Nemotron Super 49B V1.5 Strengths
- 49B parameters derived from Llama 3.3 70B with post-training
- Optimized for agentic workflows: RAG, tool calling, code
- 128K context window for complex multi-step tasks
- Competitive pricing at $0.40/$0.40 per 1M tokens
- Strong across math, code, science, and instruction following
NVIDIA: Nemotron 3 Super Strengths
- 120B MoE with only 12B active params for high efficiency
- 1M token context window for very long tasks
- Open-weight hybrid Mamba architecture
- Strong multi-agent application performance