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Model details

Gemini Pro Latest

Google Gemini Pro Latest is positioned as the current top-of-line Pro variant in Google's Gemini family of multimodal large language models, sitting between lighter Flash variants and the larger or more specialized Gemini releases. It is offered to users and developers through Gemini products, Google AI Studio, and Vertex AI, where it powers assistants, productivity tools, and custom applications that need long-context reasoning blended with tool-driven workflows. Because it carries the Pro label and is exposed as the default Pro option in Gemini APIs, it is generally aimed at workloads that require more nuanced reasoning than Flash-tier models while staying broadly deployable.

The model is built to handle extended reasoning over very long inputs while remaining flexible enough to orchestrate multi-step agentic and coding tasks, making it a fit for complex analysis, software engineering help, and orchestrated pipelines that draw on images, documents, and other media alongside text. Its very large input window relative to its output ceiling means it can absorb substantial documents or codebases and then reason or act over them in detail, which is useful for research summarization, codebase exploration, and multi-turn planning tasks. In practice, it tends to suit developers who need long-context reasoning combined with multimodal inputs and who want a stable Pro-tier default that can be reached through Google-managed endpoints as well as routed access through aggregator platforms.

OpenRouter~google/gemini-pro-latestgemini-pro

Quick Info

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Provider
OpenRouter
Model key
~google/gemini-pro-latest
Release date
Apr 27, 2026
Last updated
Apr 27, 2026
Knowledge cutoff
2025-01
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$2.00
Output token cost
$12.00

Limits

Output tokens
65,536 tokens
Context window
1,048,576 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Gemini Pro Latest

DevPass (LLM Gateway)

CoverageBenchmark

An OpenOCR rankings page reports a third-party OCR benchmark for Gemini Pro Latest, with an average score of 93.7% across 11 documents and an average latency of 19.7 seconds, measured on 2026-08-07 and published 2026-08-22. The page identifies the provider offering used as google-gemini-pro-latest(google), confirming t Per-document results include 100.0% on grocery and café receipts, 100.0% on a handwritten cursive letter, and 100.0% on handwritten notes, demonstrating strong performance on both dense numeric retail-style documents and cursive handwriting. The benchmark is narrow — OCR-specific — and tests Google's direct offering ra

DevPass (LLM Gateway)

CoveragePreview

The NanoGPT model page for the sibling Gemini 3.1 Pro Preview Low variant includes an explicit reference to the subject: "Gemini Pro Latest — google/gemini-pro-latest — Compatibility alias that routes to the newest version of Gemini Pro. Currently routes to Gemini 3.1 Pro Preview High." The page was last updated Septem Benchmarks listed on the page include GPQA Diamond at 94.1%, HLE at 47.0%, IFBench at 77.1%, T²-Bench at 95.6%, AA-LCR at 82.0%, SciCode at 58.7%, and Terminal-Bench at 53.8%, sourced from Artificial Analysis. Gateway-level pricing ($2.00 input / $12.00 output per 1M tokens) is shown but should be treated as third-part

OpenRouter

CoverageBenchmark

An independent OCR benchmark page from OpenOCR publishes reproducible performance data for Google Gemini Pro Latest served via OpenRouter. The page explicitly identifies the provider offering as "openrouter--google-gemini-pro-latest (openrouter)," matching the subject's exact model slug. Measured on the corpus ocr-shar Per-document results show strong character-level recognition on structured and unstructured inputs: grocery receipt and café receipt both scored 100.0%, handwritten letter and handwritten notes both scored 100.0%, demonstrating reliable performance on retail-style dense numeric rows and cursive handwriting transcriptio

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