Llama 3.1 Nemotron 70B Instruct

NVIDIA chattool_use

API ID: nvidia/llama-3.1-nemotron-70b-instruct

Input Price
$1.20
/1M tokens
Output Price
$1.20
/1M tokens

About Llama 3.1 Nemotron 70B Instruct

Llama 3.1 Nemotron 70B Instruct is a mid-range general-purpose model from NVIDIA with long context (131k), suitable for conversations, content creation, and general AI tasks.

๐Ÿ’ฐ
Price Ranking
#817 lowest price among 950 Chat models

Model Specifications

Context Length
131k
Max Output
16k
Release Date
2024-10-15
Capabilities
chat tool_use
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.90
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$28.80
/month
1000 tickets/day, ~800 tokens each

NVIDIA Model Lineup

Compare all models from NVIDIA to find the best fit

Model Input Output Context Capabilities
Llama 3.1 Nemotron 70B Instruct Current Free Free 131k chat 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

Similar Models from Other Providers

Cross-brand alternatives with similar capabilities

Other Aion-RP 1.0 (8B)
Input: $0.80
Output: $1.60
Context: 33k
Mistral Devstral 2 2512
Input: $0.40
Output: $2.00
Context: 262k
Moonshot AI Kimi K2 0905 (exacto)
Input: $0.40
Output: $2.00
Context: 131k
Mistral Mistral Medium 3.1
Input: $0.40
Output: $2.00
Context: 131k

๐Ÿš€ Quick Start

Get started with Llama 3.1 Nemotron 70B Instruct 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-3.1-nemotron-70b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)