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Meta: Llama 3.2 1B Instruct
meta-llama/llama-3.2-1b-instructTry Meta: Llama 3.2 1B Instruct now
Runs on your balance at the prices above. New accounts start with free usage.
One API. Every model.
Session cost $0.00
Settings
Advanced parameters
Meta: Llama 3.2 1B Instruct at a glance
- Input price is 94% lower than the median of 434 Text models.
- Context window of 60,000 tokens, enough for long documents and multi-turn conversations.
- A typical request (1,000 input / 500 output tokens) costs about $0.000446.
About Meta: Llama 3.2 1B Instruct
Meta: Llama 3.2 1B Instruct is a text generation model from Meta, part of the Llama 3.2 family. It is an instruction-tuned model with 1 billion parameters, a deliberately small size that Meta positions around efficiently performing natural language tasks. Meta released it on 25 September 2024, and its knowledge cutoff is 31 December 2023, so anything that happened after that date is outside what the model learned during training.
The model works with text only, both on input and output. It accepts a prompt and returns generated text, with a context window of 60,000 tokens and a maximum output of 54,000 tokens. That combination gives you a fairly large working space for a model of this size, enough to fit long documents or extended conversations into a single request. Meta describes its focus as summarization, dialogue and multilingual text analysis, which reflects the kind of tasks the instruction tuning targets.
Those capabilities point to a practical set of uses. Summarization is a natural fit: feed in an article, a report or a thread and ask for a shorter version. Dialogue covers chat-style assistants, question answering and simple conversational flows where the model needs to follow instructions and keep a consistent tone. Multilingual text analysis means classification, extraction or light transformation of text across languages. Because the model is small, it also suits high-volume, low-complexity jobs where you want fast responses on straightforward prompts rather than deep reasoning.
You call it through api14's OpenAI-compatible API using the model id "meta-llama/llama-3.2-1b-instruct". Because the interface follows the OpenAI format, existing OpenAI client libraries and request shapes work with only the model id and base URL changed. The request parameters it supports are frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, seed, stop, temperature, top_k and top_p. That covers the usual sampling controls, plus seed for reproducible outputs and repetition_penalty for curbing loops in longer generations.
The main thing to weigh is scale. A 1-billion-parameter model is built for efficiency, not for the hardest reasoning or the most nuanced long-form writing. If your task needs complex multi-step logic, deep domain knowledge or highly reliable instruction following on ambiguous prompts, a larger model in the Llama family or another provider will usually serve you better. If your task is summarization, dialogue or multilingual text handling at volume, this model is a reasonable default to test first.
How to call the Meta: Llama 3.2 1B Instruct API
- Create an API key in your dashboard.
- Install the official openai SDK for your language.
- Set baseURL to https://api14.com/api/v1 and model to "meta-llama/llama-3.2-1b-instruct".
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "meta-llama/llama-3.2-1b-instruct",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
Supported parameters
frequency_penaltylogit_biasmax_tokensmin_ppresence_penaltyrepetition_penaltyseedstoptemperaturetop_ktop_pSpecifications
- Context length
- 60,000
- Max output
- 54,000
- Input
- text
- Output
- text
- Knowledge cutoff
- 2023-12-31
Requests on api14 · last 7 days
Meta: Llama 3.2 1B Instruct: frequently asked questions
- How much does the Meta: Llama 3.2 1B Instruct API cost?
- Meta: Llama 3.2 1B Instruct costs Input $0.09 / 1M tokens. It is charged from your USD balance only for successful requests; failed requests are free.
- What is the context window of Meta: Llama 3.2 1B Instruct?
- Meta: Llama 3.2 1B Instruct reads up to 60,000 tokens per request: prompt, history and documents together. It writes up to 54,000 output tokens per response.
- What can Meta: Llama 3.2 1B Instruct do?
- Meta: Llama 3.2 1B Instruct accepts text and returns text.
- How do I call Meta: Llama 3.2 1B Instruct from my code?
- Point any OpenAI SDK at https://api14.com/api/v1 and set the model to "meta-llama/llama-3.2-1b-instruct". No other code changes. Copy a ready example from the code panel on this page.
- What are alternatives to Meta: Llama 3.2 1B Instruct?
- Comparable Text models at a similar price: Z.ai: GLM 5.3 Flash (batch), OpenAI: GPT-5 Nano (batch), Tencent: Hy-MT2-1.8B. Each runs through the same API key, so switching is one string.
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