Llama 3.3 Nemotron Super 49B V1.5

NVIDIA chatreasoningtool_use

API ID: nvidia/llama-3.3-nemotron-super-49b-v1.5

Input Price
$0.10
/1M tokens
Output Price
$0.40
/1M tokens

About Llama 3.3 Nemotron Super 49B V1.5

Llama 3.3 Nemotron Super 49B V1.5 is a budget-friendly general-purpose model from NVIDIA with long context (131k), suitable for conversations, content creation, and general AI tasks.

đź’°
Price Ranking
#369 lowest price among 599 Chat models

Model Specifications

Context Length
131k
Max Output
—
Release Date
2025-10-10
Capabilities
chat reasoning tool_use
Input Modalities
text
Output Modalities
text

Best For

  • Complex reasoning, math problems, multi-step logic
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
  • Simple Q&A (cheaper models available)

đź’° Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.16
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$5.10
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$7.05
/month
500 analyses/day, ~2k tokens each

NVIDIA Model Lineup

Compare all models from NVIDIA to find the best fit

Model Input Output Context Capabilities
Llama 3.3 Nemotron Super 49B V1.5 Current $0.10 $0.40 131k chat reasoning tool_use
Nemotron-4 340B Instruct Free Free 4k chat
Llama 3.1 Nemotron Nano 8B v1 Free Free 131k chat
Llama 3.3 Nemotron Super 49B v1 Free Free 131k chat
Nemotron 3 Nano 30B A3B Free Free 262k chat reasoning tool_use
Nemotron Nano 12B 2 VL Free Free 131k chat vision video

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Google Gemini 2.0 Flash
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🚀 Quick Start

Get started with Llama 3.3 Nemotron Super 49B V1.5 API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="nvidia/llama-3.3-nemotron-super-49b-v1.5",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)