Atlas / Models / Meta / meta-llama/Llama-3.2-1B-Instruct

meta-llama/Llama-3.2-1B-Instruct✓ Catalog verified

meta-llama/llama-3.2-1b-instruct

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 efficiently in low-resource environments while maintaining strong task performance. Supporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models. Click here for the original model card. Usage of this model is subject to Meta's Acceptable Use Policy.

Input price
$0.03 /1M
Output price
$0.20 /1M
Context
60K
Modalities
text
Released
Sep 25, 2024
Tool calling
Atlas signal
79/100
01

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 efficiently in low-resource environments while maintaining strong task performance. Supporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models. Click here for the original model card. Usage of this model is subject to Meta's Acceptable Use Policy.

Access: available through the official Meta API. Context window: 60K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifiermeta-llama/llama-3.2-1b-instruct
ProviderMeta
Model typeText LLM
Context window60K catalog
Input modalitiestext
Output modalitiestext
ReleasedSep 25, 2024
TokenizerLlama3
Instruction formatllama3
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltymax_tokenspresence_penaltyrepetition_penaltyseedtemperaturetop_ktop_p
Source: provider documentation + catalog feedMethodology →
03

Pricing

Live pricing components for meta-llama/llama-3.2-1b-instruct as published in the catalog.

$0.03
Input /1M
$0.20
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$2.7e-8$0.03 / 1MPer input token
Completion tokens$2e-7$0.20 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.05Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool CallingNot advertisedSupports tools / function calling
Self-Hosting✓ SupportedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

meta-llama/Llama-3.2-1B-Instruct
MMLU Signal (Reasoning)
74signal
Coding Signal (HumanEval proxy)
84signal
Math Signal (GSM8K proxy)
74signal
Science Signal (GPQA proxy)
82signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

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)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

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.