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Claude 3.7 Sonnet vs Gemma 3 4B

Compare Claude 3.7 Sonnet and Gemma 3 4B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.

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AnthropicClaude 3.7 Sonnet

Claude 3.7 Sonnet is deprecated and can no longer be run. Details and evals are still available on its model page.

GoogleGemma 3 4B
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Claude 3.7 Sonnet vs Gemma 3 4B: Overview

Claude 3.7 Sonnet

Claude 3.7 Sonnet, released by Anthropic in February 2025, is the company’s first hybrid reasoning model, combining fast response generation with an optional “extended thinking mode” that reveals longer, step-by-step reasoning. Like its predecessors, it is multimodal, handling both text and images, but expands its usability with up to 200,000 input tokens and up to 128,000 output tokens (64K generally available, 128K in beta). This makes it well-suited for analyzing large documents, codebases, or multi-turn conversations.

Typical applications include software development, research workflows, extended reasoning tasks, and enterprise-scale knowledge work where a trade-off between speed and visible reasoning is valuable.

Gemma 3 4B

Gemma 3 4B, released on March 12, 2025, is the mid-sized member of Google DeepMind’s open-weight Gemma 3 family. With about 4 billion parameters, it is multimodal—supporting text and image inputs and generating text outputs. Like the larger Gemma 3 models, it features a 128,000-token input context window with an output capacity of ~8,192 tokens, enabling it to handle long documents and mixed text–image reasoning tasks.

The 4B variant is designed as a balance between efficiency and capability: it offers multilingual support across 140+ languages, strong summarization and reasoning performance, and compatibility with moderate hardware. Inference can run with ~6.4 GB VRAM in BF16, or significantly less in quantized 8-bit (~4.4 GB) or 4-bit (~3.4 GB) modes, making it accessible to developers outside large-scale infrastructure. While it lags behind the 12B and 27B versions on the most complex reasoning and multimodal benchmarks, its lower compute footprint makes it ideal for research, prototyping, and practical deployment where efficiency matters.

Claude 3.7 Sonnet vs Gemma 3 4B Comparison Table

PropertyClaude 3.7 SonnetGemma 3 4B
OrganizationAnthropicGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2024Mar 2025
Context Window200K128K
Parameters4B
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.050
Output $/1M$0.100
Vision Tasks
CaptioningDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
Classification
Object Detection
Model Features
Multimodal Vision
Foundation Vision
LLMs with Vision Capabilities
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
37.31%
Avg Response Time16.80s
Defect Detection
60%(9/15)
Document Understanding
55.6%(5/9)
Object Counting
0%(0/10)
Object Understanding
42.9%(6/14)
Spatial Understanding
26.3%(5/19)
OCR
Overall Score
64.19%
Avg Response Time0.92s
Median input tokensincl. image tokens300
Median output tokens12
Est. cost / taskon this benchmark<$0.0001
Focused Scene OCR
63.6%(63/99)
Handwritten Math
10%(1/10)
License Plate Recognition
86.7%(26/30)
Text Recognition
73.3%(22/30)
VQA & Extraction
58.3%(35/60)