Llama 3.3 70B Instruct API
Released 2024 | 128K Tokens context | 70B params parameters
Llama 3.3 70B Instruct API enables Enterprise chat assistants, Advanced code generation and review, Long-document question answering, Summarization at scale, Retrieval-Augmented Generation (RAG), and AI agents and workflow automation. Llama 3.3 70B Instruct is a 70B-parameter open-weight large language model from Meta, optimized for instruction following, complex reasoning, and multi-turn conversations.It is well suited for enterprise use cases such as advanced chat assistants, code reasoning, and long-document analysis with large context windows. Standout strengths include High-quality reasoning and instruction adherence and Strong performance on code and analytical tasks.
from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="meta-llama/Llama-3.3-70B-Instruct", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=0.9, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n")from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="meta-llama/Llama-3.3-70B-Instruct", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=0.9, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n") Enterprise
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"Qubrid AI reduced our document processing time by over 60% and significantly improved retrieval accuracy across our RAG workflows."
Enterprise AI Team
Document Intelligence Platform