meta-llama/Llama-3.2-1B-Instruct✓ Catalog verified
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
Overview
Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate...
Access: available through the official Meta API. Context window: 60K.
Specifications
| API identifier | meta-llama/llama-3.2-1b-instruct |
| Provider | Meta |
| Model type | Text LLM |
| Context window | 60K catalog |
| Input modalities | text |
| Output modalities | text |
| Released | Sep 25, 2024 |
| Tokenizer | Llama3 |
| Instruction format | llama3 |
| Moderated | No |
| Architecture modality | text->text |
Pricing
Live pricing components for meta-llama/llama-3.2-1b-instruct as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $2.7e-8 | $0.03 / 1M | Per input token |
| Completion tokens | $2.01e-7 | $0.20 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | N/A | N/A | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$0.05Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | Not advertised | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | Not advertised | Supports tools / function calling |
| Self-Hosting | ✓ Supported | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call meta-llama/Llama-3.2-1B-Instruct through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="meta-llama/llama-3.2-1b-instruct",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| DeepSeek: R1 | DeepSeek | 64K | $0.70 | View → |
| WizardLM-2 8x22B | Microsoft | 66K | $0.62 | View → |
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does meta-llama/Llama-3.2-1B-Instruct cost?
$0.03 per 1M input tokens and $0.20 per 1M output tokens on the official Meta API.
What is the context window of meta-llama/Llama-3.2-1B-Instruct?
meta-llama/Llama-3.2-1B-Instruct supports up to 60K tokens of context.
Does meta-llama/Llama-3.2-1B-Instruct support tool / function calling?
meta-llama/Llama-3.2-1B-Instruct does not advertise first-class tool/function calling. Check vendor docs for the latest capabilities.
How do I access meta-llama/Llama-3.2-1B-Instruct?
Use the official Meta API with the model id `meta-llama/llama-3.2-1b-instruct`. See the Quick start section above for code examples.