Claude Sonnet 4 vs Gemma 3 27B

Compare Claude Sonnet 4 and Gemma 3 27B side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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AnthropicClaude Sonnet 4
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GoogleGemma 3 27B
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Claude Sonnet 4 vs Gemma 3 27B: Overview

Claude Sonnet 4

Claude 4 Sonnet, released by Anthropic in May 2025, is the mid-tier model in the Claude 4 family, designed to balance capability, cost, and speed. It is multimodal, accepting both text and images, and extends beyond prior versions with improved “computer use” support, allowing API-driven interaction with desktop-like interfaces. By default, it supports 200,000 tokens of context, but as of August 2025, it also offers a 1 million-token context window in public beta—making it one of the most context-capable models available for processing entire codebases or large document sets in a single request.

Sonnet 4 is significantly cheaper than the flagship Opus while still demonstrating strong reasoning, coding, and instruction-following ability with reduced hallucinations. Its extended context capabilities and lower latency make it well-suited for enterprise-scale knowledge management, software development, research assistants, and productivity automation where both cost efficiency and high reliability are essential.

Gemma 3 27B

Gemma 3 27B, announced on March 12, 2025, is the largest open-weight model in Google DeepMind’s Gemma 3 family. With around 27 billion parameters, it is multimodal—accepting both text and images as input and producing text outputs. It supports a 128,000-token context window and typically generates up to ~8,192 tokens, enabling it to process multi-page documents, extended conversations, or large batches of images in a single prompt.

The model is instruction-tuned in its “-it” variants for chat, reasoning, and summarization use cases, and it supports structured outputs and function calling. It is multilingual, covering over 140 languages. Deployment is flexible: the full BF16 model requires ~46 GB of VRAM, but quantization-aware training (QAT) versions in 8-bit or 4-bit reduce the footprint significantly, allowing more accessible use outside large-scale clusters. While it delivers stronger reasoning and multimodal performance than smaller Gemma models, it remains lighter and more open than proprietary systems, making it well-suited for research, development, and fine-tuned applications.

Claude Sonnet 4 vs Gemma 3 27B Comparison Table

PropertyClaude Sonnet 4Gemma 3 27B
OrganizationAnthropicGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2025Mar 2025
Context Window1.0M128K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$3.00$0.080
Output $/1M$15.00$0.160
Vision Tasks
CaptioningDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Object DetectionDemo
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Overall Score
68.66%
58.21%
Avg Response Time21.26s33.60s
Defect Detection
80%(12/15)
60%(9/15)
Document Understanding
88.9%(8/9)
77.8%(7/9)
Object Counting
20%(2/10)
10%(1/10)
Object Understanding
78.6%(11/14)
71.4%(10/14)
Spatial Understanding
68.4%(13/19)
63.2%(12/19)