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meta-llama/llama-3.3-70b-instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks. Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

Tool calling
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Specifications

Context window131K tokens
Max outputN/A
API typechat
AddedFeb 6, 2025
Model IDnovita/meta-llama/llama-3.3-70b-instruct
Data retentionYes
Used for trainingUnknown
Provider location🇺🇸 US
Privacy policyNovita AI Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model. Check the base model page or the Novita AI models overview.

Pricing

Prices updated July 24, 2026
Input / 1M
$0.39
Output / 1M
$0.39
Cache write
N/A
Cache read
N/A
Estimated cost
100K input + 10K output$0.0429
1M input + 100K output$0.43
10M input + 1M output$4.29

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to novita/meta-llama/llama-3.3-70b-instruct.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="novita/meta-llama/llama-3.3-70b-instruct",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does meta-llama/llama-3.3-70b-instruct cost?
meta-llama/llama-3.3-70b-instruct is priced at $0.39 per million input tokens and $0.39 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of meta-llama/llama-3.3-70b-instruct?
meta-llama/llama-3.3-70b-instruct has a context window of 131K tokens. That's roughly 175 words of input you can fit in a single prompt.
What can meta-llama/llama-3.3-70b-instruct do?
meta-llama/llama-3.3-70b-instruct supports tool calling. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use meta-llama/llama-3.3-70b-instruct with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "novita/meta-llama/llama-3.3-70b-instruct". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run meta-llama/llama-3.3-70b-instruct through Requesty?
Yes. meta-llama/llama-3.3-70b-instruct runs through Requesty's OpenAI-compatible API, served from Novita AI. You do not host the model yourself: point base_url at Requesty, set the model to "novita/meta-llama/llama-3.3-70b-instruct", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access meta-llama/llama-3.3-70b-instruct through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

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