llama-3-2-3b-instruct
Llama 3.2 3B is a 3-billion-parameter multilingual model from Meta, optimized for dialogue generation, reasoning and summarization.
Pricing: Input 10 credits / 1M tokens (≈ $0.05), Output 66 credits / 1M tokens (≈ $0.33).
Prices updated
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This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.
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Llama 3.2 3B Instruct API on ModelFold
Llama 3.2 3B is a 3-billion-parameter multilingual model from Meta, optimized for dialogue generation, reasoning and summarization. Try Llama 3.2 3B Instruct in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Llama 3.2 3B Instruct API
Llama 3.2 3B Instruct at a glance
Llama 3.2 3B Instruct is a chat model from Meta. It accepts text as input and returns text, with a context window of up to 131K tokens.
Use it without hosting anything
On ModelFold you call Llama 3.2 3B Instruct with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Llama 3.2 3B Instruct
Up to 131K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Llama 3.2 3B Instruct on ModelFold
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Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Llama 3.2 3B Instruct responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
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Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "llama-3-2-3b-instruct" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Llama 3.2 3B Instruct
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Low-latency experiences
Power chat interfaces, autocomplete and interactive tools where users expect fast responses.
Multilingual products
Serve users in many languages with translation, localized support replies and cross-language search.
Writing and content
Draft, edit and translate articles, emails, product copy and documentation in a consistent tone.
Frequently Asked Questions
What is Llama 3.2 3B Instruct?⌄
Llama 3.2 3B is a 3-billion-parameter multilingual model from Meta, optimized for dialogue generation, reasoning and summarization.
Which inputs does Llama 3.2 3B Instruct support?⌄
Llama 3.2 3B Instruct accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Llama 3.2 3B Instruct?⌄
Up to 131K tokens, shared between your input and the model’s output.
Does Llama 3.2 3B Instruct support function calling?⌄
Function calling is not listed for Llama 3.2 3B Instruct; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Llama 3.2 3B Instruct billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Llama 3.2 3B Instruct through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "llama-3-2-3b-instruct", using your ModelFold API key as the Bearer token.
| Input | 10 credits 1M tokens≈ $0.05 |
| Output | 66 credits 1M tokens≈ $0.33 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"llama-3-2-3b-instruct","messages":[{"role":"user","content":"Hello"}]}'