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llama-3-3-70b-instruct

⚡ Run with API

Llama 3.3 70B Instruct is Meta’s multilingual 70B text model, pretrained and instruction-tuned for dialogue use cases.

Pricing: Input 142 credits / 1M tokens (≈ $0.71), Output 142 credits / 1M tokens (≈ $0.71).

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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README
Complete guide to using Llama 3.3 70B Instruct

Llama 3.3 70B Instruct API on ModelFold

Llama 3.3 70B Instruct is Meta’s multilingual 70B text model, pretrained and instruction-tuned for dialogue use cases. Try Llama 3.3 70B Instruct in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.

What Is the Llama 3.3 70B Instruct API

Llama 3.3 70B Instruct at a glance

Llama 3.3 70B 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 3.3 70B 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 3.3 70B 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.

Function calling

Llama 3.3 70B Instruct supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.

Structured outputs

Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.

How to Use Llama 3.3 70B Instruct on ModelFold

  1. 1

    Step 1: Try it in the Playground

    Open the Playground at the top of this page, type a prompt and see how Llama 3.3 70B Instruct responds before writing any code.

  2. 2

    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.

  3. 3

    Step 3: Send a request

    Call POST https://modelfold.ai/v1/chat/completions with "model": "llama-3-3-70b-instruct" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.

  4. ✓

    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 3.3 70B Instruct

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.

Tool-calling backends

Route requests, call functions and chain API calls as the worker model inside larger agent systems.

Enterprise workflows

Automate internal processes such as reporting, knowledge-base Q&A, ticket handling and document review.

Frequently Asked Questions

What is Llama 3.3 70B Instruct?⌄

Llama 3.3 70B Instruct is Meta’s multilingual 70B text model, pretrained and instruction-tuned for dialogue use cases.

Which inputs does Llama 3.3 70B Instruct support?⌄

Llama 3.3 70B 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 3.3 70B Instruct?⌄

Up to 131K tokens, shared between your input and the model’s output.

Does Llama 3.3 70B Instruct support function calling?⌄

Yes. Llama 3.3 70B Instruct supports tools / function calling through the standard tools parameter of the chat completions API.

How is Llama 3.3 70B 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 3.3 70B Instruct through the API?⌄

Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "llama-3-3-70b-instruct", using your ModelFold API key as the Bearer token.

Rate card
Input142 credits 1M tokens≈ $0.71
Output142 credits 1M tokens≈ $0.71

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 →
Quick start
POST/v1/chat/completions
curl https://modelfold.ai/v1/chat/completions \
  -H "Authorization: Bearer $MODELFOLD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"llama-3-3-70b-instruct","messages":[{"role":"user","content":"Hello"}]}'