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Gemini 3.5 Flash vs LLaVA-1.5

Compare Gemini 3.5 Flash and LLaVA-1.5 side-by-side.

Compare Gemini 3.5 Flash vs LLaVA-1.5 live

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These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

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Gemini 3.5 Flash vs LLaVA-1.5 Comparison Table

Evals updated July 10, 2026Pricing updated July 21, 2026

PropertyGemini 3.5 FlashLLaVA-1.5
OrganizationGoogleMicrosoft
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2026Oct 2023
Context Window1.0M
Parameters7B, 13B
LicenseProprietaryCustom
Pricing per 1M tokens
Input $/1M$1.50
Output $/1M$9.00
Vision Tasks
Visual Question AnsweringDemo
captioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Multi-Label Classification
Object DetectionDemo
OCRDemo
Vision Language
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks
Overall
86.0%
Not evaluated
Object Detection
61.7%
Counting
81.1%
Identification
100.0%
OCR
91.1%
Data Extraction
94.8%
Reasoning
87.0%
Avg cost / sample$0.0082
Avg speed / sample4.8s

Gemini 3.5 Flash vs LLaVA-1.5: Overview

Gemini 3.5 Flash

Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.

Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.

LLaVA-1.5

LLaVA-1.5 is an open-source large multimodal model released in October 2023 by researchers at the University of Wisconsin-Madison and Microsoft Research. It builds on the original LLaVA architecture by introducing targeted refinements: switching the vision encoder to CLIP-ViT-L at 336-pixel resolution, replacing the projection layer with a two-layer MLP, and adding academic-task-oriented visual question answering data with response formatting prompts during training. These modifications achieve state-of-the-art performance across 11 benchmarks at release, with training completing in approximately one day on a single 8-A100 node.

The model accepts an image paired with a text prompt and generates natural language responses, supporting visual question answering, image captioning, and open-ended visual conversation. LLaVA-1.5 is available in 7B and 13B parameter variants built on the Vicuna language model, and is distributed under the Llama 2 Community License due to its Llama-2-based foundation. The original LLaVA paper was presented as an oral at NeurIPS 2023. Subsequent releases in the series (LLaVA-NeXT (LLaVA-1.6), LLaVA-NeXT-Video, and LLaVA-OneVision) are separate models with their own release pages and build on this foundation with expanded OCR, video, and multi-image capabilities.