Llama 3.1 70B Hanami x1

Other chattool_usereasoning

API ID: sao10k/l3.1-70b-hanami-x1

Input Price
$3.00
/1M tokens
Output Price
$3.00
/1M tokens

About Llama 3.1 70B Hanami x1

Llama 3.1 70B Hanami x1 is a mid-range general-purpose model from Other with standard context (16k), suitable for conversations, content creation, and general AI tasks.

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

Model Specifications

Context Length
16k
Max Output
โ€”
Release Date
2025-01-08
Capabilities
chat tool_use reasoning
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)

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$2.25
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$72.00
/month
1000 tickets/day, ~800 tokens each
Data Analysis Pipeline
$103.50
/month
500 analyses/day, ~2k tokens each

Other Model Lineup

Compare all models from Other to find the best fit

Model Input Output Context Capabilities
Llama 3.1 70B Hanami x1 Current Free Free 16k chat tool_use reasoning
Riverflow V2 Max Preview Free Free 8k chat vision image_gen
Riverflow V2 Standard Preview Free Free 8k chat vision image_gen
Riverflow V2 Fast Preview Free Free 8k chat vision image_gen
AFM 4.5B Free Free 66k chat
AFM 4.5B Free Free 66k chat

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Context: 200k
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Output: $4.40
Context: 200k
OpenAI o4 Mini High
Input: $1.10
Output: $4.40
Context: 200k
OpenAI o4 Mini
Input: $1.10
Output: $4.40
Context: 200k

๐Ÿš€ Quick Start

Get started with Llama 3.1 70B Hanami x1 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="sao10k/l3.1-70b-hanami-x1",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)