Released 72 days after Llama 3.2 11B Vision Instruct ยท All Meta releases
Llama 3.3 70B Instruct is Meta's refined large-scale model, released December 2024. With 70 billion parameters and a 65,536-token context window, it iterates on open-weight general-purpose language modeling, improving multilingual fluency, instruction adherence, and code understanding over earlier releases. The model supports tool calling and structured output for agentic workflows and programmatic integration. Its multilingual training officially spans eight languages, benefiting globally distributed teams and multi-language applications. It suits complex reasoning, long-form generation, code synthesis, and knowledge-intensive tasks where accuracy and depth matter. The open-weight release supports research fine-tuning and on-premise deployment, and it refines the 70B lineage with learnings carried over from the wider Llama family.
Llama 3.3 70B runs on 5 different routes through the qynio gateway. Compare residency, zero retention, and training posture at a glance โ full data-handling detail per route below.
Llama 3.3 70B runs on 3 independently monitored routes through the qynio gateway. A direct integration leaves you on one of them, the gateway serves whichever is healthy.
Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. 2 further routes for this model are not on the board yet and are not counted above. See uptime for every provider qynio monitors.
Each route hosting Llama 3.3 70B has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.
Zero data retention is on by default on Pay-as-you-go โ no action required. No training on customer data. EU; deposit available.
Zero data retention is on by default on Pay-as-you-go โ no action required. No training on customer data. US; wallets; deposit available.
Zero data retention is not on by default โ abuse monitoring. No training on customer data. EU; deposit available.
Zero data retention is on by default on Pay-as-you-go โ no action required. No training on customer data. US; wallets; deposit available.
Zero data retention is on by default on Pay-as-you-go โ no action required. No training on customer data. EU; deposit available.
Independent benchmark scores โ composite indices for reasoning, coding, and math, plus individual eval scores where available.
Call Llama 3.3 70B through the qynio gateway with one API key. Let your coding agent set it up, or call it directly โ qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.QYN_API_KEY,baseURL: "https://api.qyn.io/v3/compat",});const completion = await client.chat.completions.create({model: "berget/llama-3.3-70b-instruct",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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