gpt-5.1-chat-latest / image-to-text

This gpt model integrates System 2 reasoning natively. It uses an internal 'Chain of Thought' to verify logic before generating the final output. This reduces fallacies in physics and math by 40% compared to earlier models. You can control this via the reasoning_effort parameter, setting it to low, medium, or high depending on your task complexity and latency requirements.

The gpt 5.1 chat latest model supports native image and video ingestion. You can upload files up to 512MB or 1,500 individual images per request. For video, it supports up to 5 minutes of footage for temporal analysis. The model handles PNG, JPEG, WEBP, and non-animated GIF formats. For precise tasks, we recommend using the 'original' detail level to maintain high-fidelity visual understanding.

For codebase-scale refactoring, leverage the 256k context window. This gpt model is optimized for deep inheritance and cross-file dependencies. We recommend using a medium or high reasoning_effort for architectural tasks. It achieves a 94.8% on HumanEval, making it the current SOTA for software engineering. Ensure you use the streaming feature for large code generations to manage the thinking phase latency.

Reasoning_effort is a new parameter for gpt 5.1 chat latest that dictates how much compute the model spends on internal verification. 'High' effort increases accuracy for difficult logic but adds latency. 'Low' effort is better for general conversation where speed is a priority. This allows developers to balance the high costs of reasoning tokens against the need for immediate responses.

Yes, it supports native video ingestion for clips up to 5 minutes long. The model can perform motion tracking, scene description, and temporal analysis without requiring you to pre-process frames into separate images. This is ideal for security footage analysis or interactive video tutorials. Note that video processing is metered based on the number of patches generated during tokenization.

Migrating to gpt 5.1 chat latest is straightforward. Replace your existing model string with 'gpt 5.1 chat latest' in your API calls. Most parameters are backward compatible with GPT-4o. However, we strongly suggest testing your prompts with the new reasoning_effort setting and lowering your temperature to 0.0–0.5 to maintain reasoning stability during complex multi-step planning.