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Gemini 3 Flash vs Gemma 4 26B A4B

Gemini 3 Flash averages 65.7% across five Vision Evals tasks and Gemma 4 26B A4B 54.1% across four (#29 and #52 of 65 models), so Gemini 3 Flash leads overall.

  • Gemini 3 Flash wins 3 of the 4 tasks both ran, with its widest lead on counting (67.6% vs 43.2%).
  • Gemma 4 26B A4B is cheaper: $0.0019 vs $0.0024 overall average cost per sample.
  • Gemini 3 Flash is faster: 5.8s vs 27.8s per sample.

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GoogleGemini 3 Flash
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Gemini 3 Flash vs Gemma 4 26B A4B on Vision Evals

Score by taskGemini 3 FlashGemma 4 26B A4B
Counting
67.6
43.2
Reasoning
64.9
47.7
Identification
93.8
81.3
Object Detection
38.6
44.2

Roboflow Vision Evals. Full breakdown below.

Gemini 3 Flash vs Gemma 4 26B A4B Comparison Table

Evals updated October 26, 2026Pricing updated November 5, 2026

PropertyGemini 3 FlashGemma 4 26B A4B
OrganizationGoogleGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateDec 2025Apr 2026
Context Window1.0M256K
ParametersUnknown25.2B
LicenseProprietaryApache 2.0
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1M$0.500$0.025
Output $/1M$3.00$0.075
Vision Tasks
Both support 10 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
65.7%
54.1%*
Quantizationsself-hosted
BF1651.6%FP854.1%AWQ-INT452.0%hardware →
Avg cost / sample$0.0024$0.0019
Avg speed / sample5.83s27.84s
By task
Object Detection
38.6%
$0.0031
44.2%
±0.7, Mean of 3 runs, range 43.5 to 44.8
$0
Counting
67.6%
$0.0012
43.2%
±2.0, Mean of 3 runs, range 41.9 to 46.0
$0
Identification
93.8%
$0.0009
81.3%
±3.1, Mean of 3 runs, range 78.1 to 84.4
$0
OCR (low)
63.9%
$0.0024
–
by category
Single value
63.9%
Transcription
90.5%
Structured JSON
80.2%
Text localization
7.6%
OCR (high)
73.1%
$0.013
–
by category
Single value
69.1%
Transcription
90.0%
Structured JSON
87.5%
Text localization
36.9%
Reasoning (low)
64.9%
$0.0020
47.7%
±2.0, Mean of 3 runs, range 45.0 to 49.0
$0
Reasoning (high)
74.2%
$0.0040
–

Gemini 3 Flash vs Gemma 4 26B A4B: Overview

Gemini 3 Flash

Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.

The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.

Gemma 4 26B A4B

Gemma 4 26B A4B is the Mixture-of-Experts variant in Google's Gemma 4 family, with 25.2B total parameters but only 3.8B active per token. Built from the same Gemini 3 research as the 31B dense sibling and released as open weights under the Apache 2.0 license, it supports a 256K token context window with text and image input and configurable thinking mode. The "A4B" in the name refers to its approximately 4B active parameters. The MoE design makes it significantly faster at inference than the dense 31B, running nearly as fast as a 4B-parameter model while delivering roughly 97% of the dense model's quality.

For vision tasks, the 26B A4B shares the same multimodal capabilities as the 31B image understanding with variable aspect ratios and resolutions, and structured bounding box output for UI element detection. The tradeoff versus the 31B dense model is a small quality reduction in exchange for much faster inference and lower hardware requirements, fitting in 18GB of VRAM at 4-bit quantization. It ranked #6 among open models on the Arena AI text leaderboard at launch.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3 Flash performed better. It scores higher on 3 of the 4 vision tasks and averages 65.7% (#29 of 65) against 54.1% (#52 of 65) for Gemma 4 26B A4B. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Counting benchmark at low effort, Gemini 3 Flash leads with 67.6% against 43.2%. This is the widest gap between the two models across the benchmark's tasks.

Gemma 4 26B A4B is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0019 per sample against $0.0024. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 5.8s per inference against 27.8s. 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 object detection and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.