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Gemini 3.5 Flash-Lite vs GPT-5.6 Sol

Compare Gemini 3.5 Flash-Lite and GPT-5.6 Sol side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, Object Detection, and OCR.

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GoogleGemini 3.5 Flash-Lite
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OpenAIGPT-5.6 Sol
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Models in this comparison

Gemini 3.5 Flash-Lite vs GPT-5.6 Sol on Vision Evals

GPT-5.6 Sol scores higher on 4 of the six Vision Evals tasks.

The widest gap is Counting, where GPT-5.6 Sol leads 73.0% to 52.7%.

Overall, Gemini 3.5 Flash-Lite averages 69.6% (#14 of 25) against 76.9% (#9 of 25) for GPT-5.6 Sol.

Gemini 3.5 Flash-Lite is both cheaper ($0.0014 vs $0.025 per sample) and faster (2.7s vs 11.7s per sample).

Gemini 3.5 Flash-LiteGPT-5.6 Sol

Gemini 3.5 Flash-Lite vs GPT-5.6 Sol Comparison Table

Evals updated August 6, 2026Pricing updated August 11, 2026

PropertyGemini 3.5 Flash-LiteGPT-5.6 Sol
OrganizationGoogleOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateJul 2026Jul 2026
Context Window1.0M1.5M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.300$5.00
Output $/1M$2.50$30.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Video Classification
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
69.6%
76.9%
Avg cost / sample$0.0014$0.025
Avg speed / sample2.70s11.72s
By task
Object Detection
57.5%
$0.0023
68.2%
$0.045
Counting
52.7%
$0.0007
73.0%
$0.013
Identification
81.3%
$0.0004
81.3%
$0.0070
OCR
87.4%
$0.0011
90.7%
$0.032
Data Extraction
90.7%
$0.0004
82.5%
$0.0085
Reasoning (low)
48.3%
$0.0012
65.6%
$0.011
Reasoning (high)
68.9%
$0.0042
72.2%
$0.016

Gemini 3.5 Flash-Lite vs GPT-5.6 Sol: Overview

Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite is a natively multimodal reasoning model developed by Google DeepMind, released on July 21, 2026 as part of the Gemini 3.5 model family. It is the fastest model in the 3.5 series, designed for both low-latency tasks and high-throughput production workloads such as agentic search, document processing, receipt translation, and large-scale data extraction. The model accepts text, images, audio, and video as inputs, with a context window of up to 1 million tokens, and produces text output. It supports configurable thinking levels, allowing developers to tune the balance between response quality, cost, and latency depending on workload requirements.

On agentic and coding benchmarks, Gemini 3.5 Flash-Lite significantly outperforms its predecessor, Gemini 3.1 Flash-Lite, including on Terminal-Bench 2.1 (54% vs. 31%), GDM-MRCR v2 long-context (72.2% vs. 60.1%), and real-world task execution as measured by GDPval-AA v2 (1140 vs. 642). It also surpasses Gemini 3 Flash on SWE-Bench Pro (54.2% vs. 49.6%) and OSWorld-Verified (74.0% vs. 65.1%). According to the Artificial Analysis Index, the model generates output at approximately 350 tokens per second. It is built on the Gemini 3.5 Flash foundation and is evaluated across reasoning, coding, multimodal understanding, multilingual performance, and long-context tasks. The model is developed under Google's Frontier Safety Framework.

GPT-5.6 Sol

GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.

GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. On Terminal-Bench 2.1, which tests command-line agentic coding workflows, Sol Ultra achieves 91.9%. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.

Frequently Asked Questions

On Roboflow's Vision Evals, GPT-5.6 Sol performed better. It scores higher on 4 of the six vision tasks and averages 76.9% (#9 of 25) against 69.6% (#14 of 25) for Gemini 3.5 Flash-Lite. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

No. On the Vision Evals Counting benchmark, GPT-5.6 Sol leads with 73.0% against 52.7%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.5 Flash-Lite is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0014 per sample against $0.025. Gemini 3.5 Flash-Lite is priced at $0.30 per 1M input tokens and $2.50 per 1M output; GPT-5.6 Sol is priced at $5.00 per 1M input tokens and $30.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3.5 Flash-Lite is faster. Across Roboflow's Vision Evals it averaged 2.7s per inference against 11.7s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.