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Meta: Llama 3.3 70B Instruct

Meta: Llama 3.3 70B Instruct

Meta’s Open, Aligned, High-Capacity LLM for Real-World API and Self-Hosted AI

Context: 131 000 tokens
Output: 128 000 tokens
Modality:
Text
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Open-Weight, High-Performance LLM for Scalable, Aligned API Access


Llama 3.3 70B Instruct is the instruction-tuned variant of Meta’s powerful 70-billion parameter Llama 3.3 model, designed for high-quality natural language generation, reasoning, and task completion. With an open-weight license and strong alignment, it provides an accessible, production-ready alternative to proprietary LLMs.
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Ideal for developers, startups, and ML teams, Llama 3.3 70B Instruct delivers balanced performance in accuracy, coherence, and safety—accessible via API through platforms like AnyAPI.ai or deployable on-premises for full-stack control.
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Key Features of Llama 3.3 70B Instruct
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70B Parameter Model

Offers high output fluency and reasoning ability across complex prompts, thanks to its large-scale architecture and instruction-tuned training pipeline.
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Open-Weight and Self-Hostable

Available under a permissive Meta license, Llama 3.3 70B can be deployed in private cloud, VPCs, or edge environments, or accessed through AnyAPI.ai for hosted inference.
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Instruction-Tuned for Alignment

Fine-tuned to follow structured instructions, format tasks accurately, and generate safe, context-aware outputs across business, education, and development use cases.
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Strong Code and Reasoning Support

Performs well on code generation, math, and structured logic tasks, making it suitable for developer tools, assistants, and automation agents.
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Multilingual Support

Generates and understands content in 20+ languages, making it viable for international apps and localization workflows.
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Use Cases for Llama 3.3 70B Instruct
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AI Copilots and Coding Assistants

Deploy Llama 3.3 70B Instruct in dev environments to write code, explain snippets, and assist with debugging in Python, JavaScript, and more.
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Internal Knowledge Tools and RAG

Pair with vector databases to enable enterprise-grade retrieval-augmented generation (RAG) systems for support, compliance, or documentation.
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Instruction-Following AI Agents

Build structured task agents for scheduling, CRM updates, and email drafting with a reliable understanding of input prompts.
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Content Generation for Marketing or Docs

Produce articles, descriptions, summaries, and FAQs at scale, with more control than generic generative models.
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Chatbots and Multilingual Interfaces

Use in user-facing chatbots that require consistency, memory, and instruction following in English, Spanish, French, and more.


Why Use Llama 3.3 70B Instruct via AnyAPI.ai
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API Access Without Hosting Overhead

Access Llama 3.3 70B Instruct through a fully managed API—no need to spin up your own inference clusters.
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Unified API Across Open and Proprietary Models

Compare and switch between Llama, GPT, Claude, and Gemini using one SDK and one billing model.
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No Vendor Lock-In

Enjoy the freedom of open weights with the convenience of AnyAPI.ai’s infrastructure.
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Usage-Based Billing and Analytics

Track usage, manage tokens, and scale with demand using built-in analytics and transparent pricing.
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Superior to OpenRouter or AIMLAPI

AnyAPI.ai offers better provisioning, support, and visibility across all supported LLMs, including Meta’s models.


Start Using Llama 3.3 70B Instruct via AnyAPI.ai
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Llama 3.3 70B Instruct is a powerful, aligned, and fully open LLM—ready to power real-world apps at scale.

Integrate Llama 3.3 70B Instruct via AnyAPI.ai and start building reliable AI tools today.

Sign up, get your API key, or deploy it locally with full control.

Comparison with other LLMs

Model
Context Window
Multimodal
Latency
Strengths
Model
Meta: Llama 3.3 70B Instruct
Context Window
131k
Multimodal
No
Latency
Fast
Strengths
Open-weight, aligned, coding + reasoning
Get access
Model
OpenAI: GPT-4 Turbo
Context Window
128k
Multimodal
Yes
Latency
Very High
Strengths
Production-scale AI systems
Get access
Model
Anthropic: Claude 4 Sonnet
Context Window
200
Multimodal
Yes
Latency
Very Fast
Strengths
Speed, alignment, long memory
Get access
Model
Mistral: Mistral Large
Context Window
128k
Multimodal
No
Latency
Fast
Strengths
Open-weight, cost-efficient, customizable
Get access
Model
Google: Gemini 2.5 Flash
Context Window
1mil
Multimodal
Yes
Latency
Ultra Fast
Strengths
Image+text input, low cost, real-time use
Get access

Sample code for 

Meta: Llama 3.3 70B Instruct

Python
JavaScript
Curl
import requests

url = "https://api.anyapi.ai/v1/chat/completions"

payload = {
    "stream": False,
    "tool_choice": "auto",
    "logprobs": False,
    "model": "llama-3.3-70b-instruct",
    "messages": [
        {
            "role": "user",
            "content": "Hello"
        }
    ]
}
headers = {
    "Authorization": "Bearer AnyAPI_API_KEY",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
import requests url = "https://api.anyapi.ai/v1/chat/completions" payload = { "stream": False, "tool_choice": "auto", "logprobs": False, "model": "llama-3.3-70b-instruct", "messages": [ { "role": "user", "content": "Hello" } ] } headers = { "Authorization": "Bearer AnyAPI_API_KEY", "Content-Type": "application/json" } response = requests.post(url, json=payload, headers=headers) print(response.json())
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const url = 'https://api.anyapi.ai/v1/chat/completions';
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'},
  body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"llama-3.3-70b-instruct","messages":[{"role":"user","content":"Hello"}]}'
};

try {
  const response = await fetch(url, options);
  const data = await response.json();
  console.log(data);
} catch (error) {
  console.error(error);
}
const url = 'https://api.anyapi.ai/v1/chat/completions'; const options = { method: 'POST', headers: {Authorization: 'Bearer AnyAPI_API_KEY', 'Content-Type': 'application/json'}, body: '{"stream":false,"tool_choice":"auto","logprobs":false,"model":"llama-3.3-70b-instruct","messages":[{"role":"user","content":"Hello"}]}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); }
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Code is copied
curl --request POST \
  --url https://api.anyapi.ai/v1/chat/completions \
  --header 'Authorization: Bearer AnyAPI_API_KEY' \
  --header 'Content-Type: application/json' \
  --data '{
  "stream": false,
  "tool_choice": "auto",
  "logprobs": false,
  "model": "llama-3.3-70b-instruct",
  "messages": [
    {
      "role": "user",
      "content": "Hello"
    }
  ]
}'
curl --request POST \ --url https://api.anyapi.ai/v1/chat/completions \ --header 'Authorization: Bearer AnyAPI_API_KEY' \ --header 'Content-Type: application/json' \ --data '{ "stream": false, "tool_choice": "auto", "logprobs": false, "model": "llama-3.3-70b-instruct", "messages": [ { "role": "user", "content": "Hello" } ] }'
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Code is copied
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FAQs

Answers to common questions about integrating and using this AI model via AnyAPI.ai

What is Llama 3.3 70B Instruct best used for?

It’s ideal for internal copilots, RAG applications, developer tools, and instruction-following agents in production.

Is Llama 3.3 70B Instruct open-weight?

Yes. It can be downloaded and self-hosted or accessed via AnyAPI.ai with full licensing clarity.

How does it compare to GPT-4 Turbo or Claude?

It offers similar performance for many instruction tasks and code generation, but at lower cost and with full self-hosting flexibility.

Can I fine-tune Llama 3.3 70B?

Yes. As an open-weight model, it can be further fine-tuned or prompt-engineered for domain-specific tasks.

Is it safe for production use?

Yes. It has been aligned for safety and instruction-following, and supports integration into trusted AI systems.

Still have questions?

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