Llama 3.3 Nemotron Super 49B V1.5

NVIDIA chatreasoningtool_use

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

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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
#675 lowest price among 950 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
Calculate Your Custom Usage

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 Free Free 131k chat reasoning tool_use
Nemotron-4 340B Instruct Free Free 4k chat
Nemotron-4 340B Instruct Free Free 4k chat
Llama 3.1 Nemotron Nano 8B v1 Free Free 131k chat
Llama 3.1 Nemotron Nano 8B v1 Free Free 131k chat
Llama 3.3 Nemotron Super 49B v1 Free Free 131k chat
View All NVIDIA Models →

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đź’ˇ Cheaper Alternatives

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$0.04 $0.16 131k
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$0.05 $0.20 262k
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$0.06 $0.24 262k

Cross Brand

GTE-Base Other
$0.0050 Free 512
E5-Base-v2 Other
$0.0050 Free 512
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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)

Resources

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