CodeLlama 34B Instruct

Meta chatcode Free

API ID: meta-llama/codellama-34b-instruct

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

About CodeLlama 34B Instruct

CodeLlama 34B Instruct is Meta's balanced code model, offering strong programming capability in a more deployable package. With 34 billion parameters, it delivers excellent performance on coding tasks while being feasible to run on high-end consumer hardware. The model excels at code generation, completion, and explanation across popular programming languages. CodeLlama 34B features efficient architecture that enables practical deployment for development tools and coding assistants. Its open weights support fine-tuning for specific languages or codebases. The model is ideal for organizations seeking capable coding AI without the resources required for 70B models. For developers building code-focused applications with moderate compute budgets, CodeLlama 34B provides excellent capability-to-resource ratio. It's particularly popular for local development assistants and enterprise tools requiring on-premise deployment.

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

Model Specifications

Context Length
8k
Max Output
โ€”
Release Date
2023-08-20
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

Compare all models from Meta to find the best fit

Model Input Output Context Capabilities
CodeLlama 34B Instruct Current Free Free 8k chat code
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๐Ÿš€ Quick Start

Get started with CodeLlama 34B 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-34b-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)