Meta: Llama 3.2 3B Instruct

by Meta

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages. Trained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings. Click here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD.md). Usage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

Avg Score

53.9%

260 answers

Avg Latency

3.0s

25 runs

Pricing

Free

input

Free

output

per 1M tokens

Context

131K

tokens

Alternatives

Models with similar or better quality but different tradeoffs

Same Quality, Cheaper

Models with similar or better performance at a lower cost per token.

No alternatives found

Same Quality, Faster

Models with similar or better performance but lower latency.

Model	Latency
Google: Gemini 2.5 Flash Lite	-62%
Google: Gemini 2.0 Flash	-58%
Google: Gemini 2.5 Flash	-51%
Mistral: Ministral 3 8B 2512	-44%
Mistral: Ministral 3 3B 2512	-43%

Same Cost, Better

Models at a similar price point with higher benchmark scores.

No alternatives found

Other Models from Meta

Compare performance with other models from the same creator

Model	Score	Latency	Cost/1M
Meta: Llama 4 Maverick	76.4%	2.6s	$0.38
Meta: Llama 4 Scout	74.3%	2.8s	$0.19
Meta: Llama 3.3 70B Instruct	71.7%	3.5s	$0.21
Meta: Llama 3.2 1B Instruct	39.3%	4.4s	$0.11
Meta: Llama 3.1 405B (base)	3.2%	45.0s	$4.00
Meta: Llama Guard 4 12B	—	—	$0.18
Llama Guard 3 8B	—	—	$0.04
Meta: Llama 3.3 70B Instruct	—	—	$0.0000
Meta: Llama 3.2 90B Vision Instruct	—	—	$0.38
Meta: Llama 3.2 11B Vision Instruct	—	—	$0.05
Meta: Llama 3.1 8B Instruct	—	—	$0.03
Meta: Llama 3.1 405B Instruct	—	—	$0.0000
Meta: Llama 3.1 405B Instruct	—	—	$3.50
Meta: Llama 3.1 70B Instruct	—	—	$0.40
Meta: LlamaGuard 2 8B	—	—	$0.20
Meta: Llama 3 70B Instruct	—	—	$0.35
Meta: Llama 3 8B Instruct	—	—	$0.04

Benchmark Performance

How this model performs across different benchmarks

Benchmark	Score	Rank
Math Bench: Addition (1-10)	100.0%	10 / 35
Math Bench: Subtraction (1-10)	100.0%	12 / 35
Math Bench: Multiplication (1-10)	100.0%	12 / 35
Structured Customer Support Extraction	100.0%	6 / 17
Repetitive Onomatopoeia Response Benchmark	100.0%	4 / 17
SaaS Customer Support Extraction and Strategy	90.0%	16 / 17
Math Bench: Division (1-10)	87.0%	31 / 35
Math Bench: Arithmetic (1-100)	85.0%	31 / 35
Motor production test	85.0%	34 / 36
Math Bench: Arithmetic (1-1000)	70.0%	31 / 35
KUKA force Torque control programming skills	70.0%	16 / 17
Customer support	40.0%	15 / 17
Product Recommendations	37.5%	34 / 36
Venture Capital Terms Benchmark	33.6%	24 / 25
Karlsruhe Local Knowledge Benchmark	33.3%	32 / 35
Character Frequency Bench	25.5%	33 / 35
Spatial Reasoning: Germany	21.4%	33 / 35
Customer service	20.0%	16 / 17
solve n-queens in clojure in one shot	10.0%	16 / 16
German Memelord Bench	3.8%	33 / 35
Money Boy Cultural Literacy Test	0.0%	31 / 35
Karl Lorey knowlege	0.0%	35 / 36
Current Global Political Leaders	0.0%	16 / 17

Price vs Performance

Compare cost efficiency across all models

Current model

Other models

X-axis uses log scale for better visualization of price range

Score Over Time

Performance trends across all benchmark runs

Benchmark Activity

Number of benchmark runs over time

Quickstart

Get started with this model using OpenRouter

View on OpenRouter

import { OpenRouter } from "@openrouter/sdk";

const openrouter = new OpenRouter({
  apiKey: "<OPENROUTER_API_KEY>"
});

const completion = await openrouter.chat.completions.create({
  model: "meta-llama/llama-3.2-3b-instruct:free",
  messages: [
    {
      role: "user",
      content: "Hello!"
    }
  ]
});

console.log(completion.choices[0].message.content);

Get your API key at openrouter.ai/keys