Nemotron 3 Ultra
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...
Context window
This model accepts 1M tokens in one request (~750K words of text).
What fits in one request
- FitsShort documentAbout 1,500 words of text
- FitsLong documentAbout 37K words of text
- FitsSmall codebaseAbout 150K words of text
- FitsFull novelAbout 375K words of text
Specifications
Context size, pricing, and release info in one place.
- Context window
- 1,000,000 tokens (1M)
- Max output tokens
- 16,384 tokens (16K)
- Speed tier
- balanced
- Provider
- Nvidia
- Release date
- Jun 2026
Capabilities
See which features this model supports, such as vision, tools, and streaming.
- Tool use
- Can call external tools and APIs
- Supported
- Function calling
- Structured function call interface
- Supported
- Extended thinking
- Shows its chain-of-thought reasoning
- Supported
- Streaming
- Returns tokens as they are generated
- Supported
- Prompt caching
- Reuse repeated prompt prefixes cheaply
- Supported
- Vision
- Accepts image inputs alongside text
- Not supported
- Web search
- Can browse the web during a request
- Not supported
- Batch API
- Process many requests asynchronously
- Not supported
Best for
Jump to a guide or ranking that matches each workload.
Compare Nemotron 3 Ultra
Open a side-by-side comparison with one click.
- Nemotron 3 Ultra vs Jp Anthropic Claude Sonnet 4 6
Same context window size
- Nemotron 3 Ultra vs Amazon Titan Text Express
Nemotron 3 Ultra has 2280% larger context window
- Nemotron 3 Ultra vs Amazon Titan Text Premier
Nemotron 3 Ultra has 2280% larger context window
- Nemotron 3 Ultra vs Amazon Titan Text Lite
Nemotron 3 Ultra has 2280% larger context window
- Nemotron 3 Ultra vs Apac Amazon Nova 2 Lite
Same context window size
- Nemotron 3 Ultra vs Apac Amazon Nova 2 Pro Preview 20251202
Same context window size
Frequently asked questions
Short answers about context size and how this model behaves.
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