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
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
Performance
Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.
Performance trends
Availability
Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.
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.