Jan. 30, 2026 — Google has announced Agentic Vision, a new capability in Gemini 3 Flash that turns image understanding into an active, tool-using workflow rather than a single “static glance.”
Agentic Vision pairs visual reasoning with code execution (Python) so the model can iteratively zoom in, crop, annotate, and otherwise manipulate an image to verify details before responding—helping reduce guesswork on fine-grained elements like serial numbers or distant text.
According to Google DeepMind, this approach follows a “Think, Act, Observe” loop: the model forms a multi-step plan, executes Python to transform or analyze the image, then appends the transformed output back into its context window to support a more grounded final answer.
Google reports that enabling code execution with Gemini 3 Flash delivers a consistent 5–10% quality boost across most vision benchmarks. The company also highlights early developer use cases, including iterative inspection of high-resolution documents (e.g., building-plan validation) and “visual scratchpad” style annotation to reduce counting and localization errors.
Beyond inspection and annotation, Agentic Vision can offload multi-step visual arithmetic to a deterministic Python environment—parsing dense visual tables, normalizing values, and generating charts (e.g., with Matplotlib) rather than relying on probabilistic reasoning alone.
Availability and next steps
Agentic Vision is available now via the Gemini API in Google AI Studio and Vertex AI, and is beginning to roll out in the Gemini app (via the “Thinking” model selection). Google says it plans to make more code-driven behaviors implicit over time, expand tooling (including ideas like web and reverse image search), and bring the capability to additional model sizes beyond Flash.
Original announcement (with full details and examples): Google’s blog post.
