CodeLlama 70B Instruct

Meta chatcode Free

API ID: meta-llama/codellama-70b-instruct

Input Price
Free
/1M tokens
Output Price
Free
/1M tokens

About CodeLlama 70B Instruct

CodeLlama 70B Instruct is Meta's largest code-specialized model, delivering exceptional performance on programming tasks. With 70 billion parameters trained extensively on code, it excels at code generation, completion, explanation, and debugging across dozens of programming languages. The model features a 16K context window optimized for code and demonstrates strong performance on HumanEval and other coding benchmarks. CodeLlama 70B supports infilling for IDE integrations and can generate complete implementations from natural language descriptions. Its open weights enable fine-tuning for specific programming domains and on-premise deployment. The model is particularly valuable for enterprise development tools, code review automation, and AI-powered programming assistants. For organizations seeking capable open-source coding AI, CodeLlama 70B offers strong performance with full deployment control. It remains popular despite newer models, particularly for applications requiring proven reliability.

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Price Ranking
#1 lowest price among 950 Chat models โ€” Top 20% cheapest!

Model Specifications

Context Length
2k
Max Output
โ€”
Release Date
2024-01-30
Capabilities
chat code
Input Modalities
text
Output Modalities
text

Best For

  • Code generation, debugging, code review, refactoring
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
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This model is completely free!

No token costs - use it without worrying about API bills.

Estimate Token Usage

Meta Model Lineup

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๐Ÿš€ Quick Start

Get started with CodeLlama 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="meta-llama/codellama-70b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)