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Claude Sonnet 4.6 vs Gemma 4 26B A4B

Compare Claude Sonnet 4.6 and Gemma 4 26B A4B side-by-side. See how these vision models stack up in Image Captioning, Classification, Open Prompt, Object Detection, and OCR.

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AnthropicClaude Sonnet 4.6
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GoogleGemma 4 26B A4B
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Claude Sonnet 4.6 vs Gemma 4 26B A4B Comparison Table

Evals updated October 7, 2026Pricing updated October 7, 2026

PropertyClaude Sonnet 4.6Gemma 4 26B A4B
OrganizationAnthropicGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Apr 2026
Context Window1.0M256K
ParametersUnknown25.2B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$3.00$0.090
Output $/1M$15.00$0.300
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 6 vision tasks
OverallNot evaluated
63.6%
Quantizationsself-hosted
BF1661.9%FP863.6%AWQ-INT461.6%hardware →
Avg cost / sample–$0.0019
Avg speed / sample–27.84s
By task
Object Detection–
44.2%
±0.7, Mean of 3 runs, range 43.5 to 44.8
$0
Counting–
43.2%
±2.0, Mean of 3 runs, range 41.9 to 46.0
$0
Identification–
81.3%
±3.1, Mean of 3 runs, range 78.1 to 84.4
$0
OCR–
88.7%
±1.3, Mean of 3 runs, range 87.6 to 90.2
$0
Data Extraction–
76.6%
±0.5, Mean of 3 runs, range 76.3 to 77.3
$0
Reasoning–
47.7%
±2.0, Mean of 3 runs, range 45.0 to 49.0
$0

Claude Sonnet 4.6 vs Gemma 4 26B A4B: Overview

Claude Sonnet 4.6

Claude Sonnet 4.6 is Anthropic's mid-tier large language model, released February 17, 2026, designed to balance performance, cost, and versatility for professional and developer use. It supports text and vision-based tasks with advanced reasoning, agentic capabilities, and Adaptive Thinking — a mode where the model dynamically scales its internal reasoning depth. A beta context window of up to 1,000,000 tokens (200K standard) enables processing of entire codebases or document collections in a single request. Parameters are undisclosed.

Optimized for coding, computer use, long-context reasoning, agent planning, and knowledge work, Sonnet 4.6 delivers a full generational upgrade over Sonnet 4.5 and approaches Opus 4.5-level performance across many benchmarks at a fraction of the cost. It is the default model on Claude.ai, Claude Cowork, and is available via API and major cloud platforms — making it well suited for production workloads requiring strong reasoning without flagship pricing.

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.