Meta: Llama 3.2 1B Instruct

Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants

Model lab: Meta
Model family: llama

Model resources

Hugging Face

Modalitiestext → text

Context window131,072

Maximum output32,000

Input · Context ≤ 60000 tokens · Maximum output 32000 tokensUSD 0.0216 / 1M tokens

Output · Context ≤ 60000 tokens · Maximum output 32000 tokensUSD 0.1608 / 1M tokens

Try now

Quickstart

Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to meta/llama-3.2-1b-instruct.

import os
import requests

base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "meta/llama-3.2-1b-instruct"

response = requests.post(
    f"{base_url}/chat/completions",
    headers={
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json",
    },
    json={
        "model": model_id,
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
    timeout=60,
)
response.raise_for_status()
print(response.json())

Use the familiar OpenAI-style chat request format to make model integration easier.

Llama 3.2 1B Instruct API Pricing

Type	Price information
Input · Context ≤ 60000 tokens · Maximum output 32000 tokens	USD 0.0216 / 1M tokens
Output · Context ≤ 60000 tokens · Maximum output 32000 tokens	USD 0.1608 / 1M tokens

Benchmarks

Intelligence Index · v4.34.8

Coding Index—

Agentic Index—

Performance

Performance trends

Throughput89.9 tok/sCurrent

Time to first token1.4 sCurrent

End-to-end latency7.8 sCurrent

Throughput

Current89.9 tok/s

Window average89.9 tok/s

Time to first token

Current1.4 s

Window average1.4 s

End-to-end latency

Current7.8 s

Window average7.5 s

Tail latency (P99)

Current13.0 s

Window average16.7 s

Prompt cache hit rate

Current26.1%

Window average23.3%

Error rate

Current0.0%

Window average0.2%

Availability

Uptime100%At least one provider responded

Availability100%Requests actually served

Error rate0%Share of failed requests

Served requests, hour by hour

24 hours agoNow

Llama 3.2 1B Instruct Compare models

Model	Input price	Output price	Context window	Capabilities
Llama 3.2 1B InstructThis page	USD 0.0216 / 1M tokens · Context ≤ 60000 tokens · Maximum output 32000 tokens	USD 0.1608 / 1M tokens · Context ≤ 60000 tokens · Maximum output 32000 tokens	131,072	Text output · Tool calling
Llama-3.3-70B-Instruct	USD 0.08 / 1M tokens	USD 0.256 / 1M tokens	128,000	Text output · Tool calling
Llama-3.2-1B	USD 0.08 / 1M tokens	USD 0.08 / 1M tokens	131,072	Text output
Llama-3.2-3B	USD 0.08 / 1M tokens	USD 0.08 / 1M tokens	131,072	Text output
Llama-3.1-8B-Instruct	USD 0.016 / 1M tokens	USD 0.032 / 1M tokens	128,000	Text output · Tool calling

Model specifications

Input: text
Output: text
Context window: 131,072
Maximum output: 32,000
Release date: 2024-09-25
Attachments: No
Reasoning: No
Tool calling: Yes
Temperature setting: Yes
Open weights: Yes

Frequently asked questions

What is Llama 3.2 1B Instruct for?

Compact instruction-tuned Llama model for multilingual dialogue and on-device assistants

What inputs and outputs does Llama 3.2 1B Instruct support?

Recorded inputs: text; outputs: text.

How is Llama 3.2 1B Instruct priced?

The pricing table shows the current recorded Moduck price. For example: Input · Context ≤ 60000 tokens · Maximum output 32000 tokens USD 0.0216 / 1M tokens; Output · Context ≤ 60000 tokens · Maximum output 32000 tokens USD 0.1608 / 1M tokens. See the pricing table for all units, variants, and conditions.

What specifications are recorded for Llama 3.2 1B Instruct?

Current model records list Context window 131,072 tokens; Maximum output 32,000 tokens.

What model parameter does the Quickstart use?

The example uses meta/llama-3.2-1b-instruct. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.

Can I call this model through the Moduck API now?

This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.