GPT OSS 120B API
Released August 2024 | 256k Tokens context | 121.7B Params parameters
GPT OSS 120B API enables Autonomous agents and multi-step reasoning, Advanced function calling and workflow orchestration, Research-grade problem solving and planning, Enterprise automation across verticals, Large-scale code generation and debugging, R&D assistance and scientific exploration, Conversational AI and smart copilots, Knowledge extraction and document understanding, Long-context business intelligence and analytics, and Custom fine-tuning for domain-specific performance. Introducing gpt-oss-120B, OpenAI's flagship open-weight model in the gpt-oss series, built for advanced reasoning, large-scale agentic workloads, and enterprise-grade automation. With 120B parameters and a highly optimized Mixture-of-Experts (MoE) architecture, it activates 12B parameters during inference, delivering exceptional intelligence while maintaining competitive latency. Designed for complex reasoning, multi-task agents, and long-horizon planning, gpt-oss-120B brings frontier-level capability to commercial and self-hosted deployments. Standout strengths include High-capacity MoE design for strong reasoning and generalization and Optimized activation load for high throughput (12B active parameters). It is optimized for production agent and assistant workloads where response quality, latency, and predictable operating cost all matter.
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="openai/gpt-oss-120b", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=1, 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="openai/gpt-oss-120b", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.7, top_p=1, 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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