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Claude Opus 4 vs Gemma 3 4B

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

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AnthropicClaude Opus 4

Claude Opus 4 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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Models in this comparison

Anthropic

Claude Opus 4 vs Gemma 3 4B: Overview

Claude Opus 4

Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.

Positioned at the high end of Anthropic’s offerings, Opus 4 achieves state-of-the-art results on coding benchmarks like SWE-Bench (72.5%) and Terminal-Bench (43.2%). It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.

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 Opus 4 vs Gemma 3 4B Comparison Table

PropertyClaude Opus 4Gemma 3 4B
OrganizationAnthropicGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2025Mar 2025
Context Window200K128K
Parameters4B
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$15.00$0.050
Output $/1M$75.00$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
56.72%
37.31%
Avg Response Time19.74s16.80s
Defect Detection
66.7%(10/15)
60%(9/15)
Document Understanding
88.9%(8/9)
55.6%(5/9)
Object Counting
0%(0/10)
0%(0/10)
Object Understanding
64.3%(9/14)
42.9%(6/14)
Spatial Understanding
57.9%(11/19)
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)