How much does the Llama 3.2 3B Instruct API cost?

On FastMetal, Llama 3.2 3B Instruct is billed per token: $0.056 per 1M input tokens and $0.3685 per 1M output tokens on a US-dollar account, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.

Can I call Llama 3.2 3B Instruct with the OpenAI SDK?

Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "llama-3.2-3b-instruct" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.

What is the context window of Llama 3.2 3B Instruct?

131,072 tokens, shared between the prompt and the response.

What do I need to try Llama 3.2 3B Instruct?

Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.

Back to Models

Llama 3.2 3B Instruct

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages. Trained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings. Click here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md). Usage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

9/25/2024

131,072 tokens

Input: $0.056/M

Output: $0.3685/M

Try in Chat Get API Key

Specifications

Modalities

Input

text

Output

text

Supported Parameters

frequency_penalty

logit_bias

max_tokens

min_p

presence_penalty

repetition_penalty

response_format

seed

stop

temperature

top_k

top_p

Max Output Tokens

16,384

Data policy

Prompt retention: Not retained — every host this model runs on is configured not to retain prompts
Training: Not used for training

Whether a provider trains on prompts is a declared value from our terms with them. Retention is determined from the upstream listing for every host this model can reach. Neither is guessed.

Measured performance

Time to first response (p50)3.5s

Throughput (p50)100000 tokens/s

Measured through FastMetal's own gateway over the last 30 days (659 first-response samples).

Throughput is sampled once a day: the median of 27 observations over the last 30 days.

Time to first response is measured to the first streamed chunk; throughput counts all output tokens, including reasoning tokens. These are observations, not a performance guarantee.

Code Examples

curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "llama-3.2-3b-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

How Llama 3.2 3B Instruct actually answers

Real responses to our standard prompts, recorded on FastMetal.

Count the number of 'r's in 'strawberry'

Count the number of 'r's in 'strawberry'. Explain your reasoning step by step.

To count the number of 'r's in 'strawberry', I will follow these steps: 1. I will examine the word "strawberry" one letter at a time. 2. I will identify each letter individually. 3. I will check if each letter is an 'r'. Here's the word "strawberry" broken down: S - T - R - A - W - B - E - R - R - Y Now, I will count the 'r's: There is one 'R' in the first position. There is another 'R' in the ninth position. So, there are 2 'r's in the word "strawberry".

2.7s response142 output tokens

Debug This Error

I'm getting the following error in my Node.js application: TypeError: Cannot read properties of undefined (reading 'map') at UserList (/app/components/UserList.js:12:25) at renderWithHooks (/app/node_modules/rea…

**Error Explanation** The error "Cannot read properties of undefined (reading 'map')" indicates that the `users` prop is `undefined` when the `UserList` component is rendered. This means that the `users` prop is not being passed to the component from its parent component. **Solution** To fix this issue, you need to ensure that the `users` prop is being passed to the `UserList` component from its parent component. Here are a few possible solutions: ### 1. Pass `users` as a prop from the parent component In your parent component, make sure to pass the `users` array as a prop to the `UserList` component: ```jsx import React from 'react'; import UserList from './UserList'; const App = () =…

3.8s response504 output tokens

Code Review

Please review the following Python function and suggest improvements for readability, performance, and best practices: def get_data(url, retries=3): import requests import time for i in range(retries):…

**Improved Code** ```python import requests import time import logging def get_data(url: str, retries: int = 3) -> list: """ Retrieves data from a given URL, handling retries and timeouts. Args: url (str): The URL to retrieve data from. retries (int, optional): Number of retries. Defaults to 3. Returns: list: A list of dictionaries containing active data. """ logger = logging.getLogger(__name__) logger.info(f"Retrieving data from {url}") for attempt in range(retries): try: response = requests.get(url, timeout=10) response.raise_for_status() # Raise an exception for bad status codes data =…

2.1s response533 output tokens

Compare these answers side by side with other models →

Frequently asked questions

How much does the Llama 3.2 3B Instruct API cost?: On FastMetal, Llama 3.2 3B Instruct is billed per token: $0.056 per 1M input tokens and $0.3685 per 1M output tokens on a US-dollar account, before tax. Usage is drawn from a prepaid balance; there is no subscription or monthly fee.
Can I call Llama 3.2 3B Instruct with the OpenAI SDK?: Yes. Point base_url at https://api.fastmetal.ai/v1 and pass "llama-3.2-3b-instruct" as the model; existing OpenAI-style code works unchanged, including streaming, tool calls and structured output.
What is the context window of Llama 3.2 3B Instruct?: 131,072 tokens, shared between the prompt and the response.
What do I need to try Llama 3.2 3B Instruct?: Create an account and add credit; the model is then available both in the browser chat and over the API. There is no contract or minimum spend.