OpenAI's 3.6.0 Python package includes a new `gpt-4o-2024-08-06` model ID, beta real-time

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Aug 28, 2026 23:16 UTC pypi openai

OpenAI's 3.6.0 Python package includes a new `gpt-4o-2024-08-06` model ID, beta real-time and responses connection features, and mTLS endpoints, suggesting new model and API capabilities.

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openai's latest python package (v3.6.0) just dropped, and it includes a new model id: `gpt-4o-2024-08-06`. looks like a new gpt-4o variant is coming!

interesting find in openai's new sdk: `client.beta.realtime.connect()` and `client.beta.responses.connect()` alongside new mtls endpoints. could openai be rolling out new real-time api capabilities?

openai 3.5.0 -> 3.6.0: +91 strings, -553 strings, 43 interesting [model_id] (1) + py with client.chat.completions.stream( model="gpt-4o-2024-08-06", messages=[...], ) as stream: for event in stream: if event.type == "content.delta": print(event.delta, flush=True, end="") [feature_flag] (4) + py connection = client.beta.realtime.connect(...).enter() # ... connection.close() + py connection = client.beta.responses.connect(...).enter() # ... connection.close() + py connection = client.beta.realtime.connect(...).enter() # ... connection.close() + py connection = client.beta.responses.connect(...).enter() # ... connection.close() [endpoint] (2) + https://mtls-eu.api.openai.com/v1 + https://mtls-us.api.openai.com/v1 [sentence] (41) + py with client.chat.completions.stream( model="gpt-4o-2024-08-06", messages=[...], ) as stream: for event in stream: if event.type == "content.delta": print(event.delta, flush=True, end="") + py connection = client.beta.realtime.connect(...).enter() # ... connection.close() + py connection = client.beta.responses.connect(...).enter() # ... connection.close() + py connection = client.beta.realtime.connect(...).enter() # ... connection.close() + py connection = client.beta.responses.connect(...).enter() # ... connection.close() + - Based on your data it seems like you're trying to fine-tune a model for {ft_type} - For classification, we recommend you try one of the faster and cheaper models, such as `ada` - For classification, you can estimate the expected model performance by keeping a held out dataset, which is not used fo + - There are {len(long_indexes)} examples that are very long. These are ro