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Claude Opus 4 vs Gemma 3 12B

Compare Claude Opus 4 and Gemma 3 12B 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 12B
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Models in this comparison

Anthropic

Claude Opus 4 vs Gemma 3 12B: 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 12B

Gemma 3 12B, announced by Google DeepMind on March 12, 2025, is part of the open-weight Gemma 3 family, designed to provide a balance between capability and accessibility. With around 12 billion parameters, it supports multimodal input (text + images) and outputs text, making it useful for reasoning, summarization, Q&A, and visual understanding tasks. The model supports an input context of 128,000 tokens and typically generates up to ~8,000 tokens in output.

The 12B variant is instruction-tuned (“Gemma-3-12B-IT”) and optimized for multilingual use across more than 140 languages. It can run on a single GPU or TPU, offering a lighter compute footprint than very large proprietary models, while still achieving strong performance in reasoning benchmarks. Quantized and lower-precision variants are available to improve efficiency. Limitations include smaller output lengths relative to input capacity, scaling hardware needs at larger sizes, and performance below massive proprietary models on the most complex multimodal or reasoning-heavy tasks.

Claude Opus 4 vs Gemma 3 12B Comparison Table

PropertyClaude Opus 4Gemma 3 12B
OrganizationAnthropicGoogle
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2025Mar 2025
Context Window200K128K
Parameters12B
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$15.00$0.050
Output $/1M$75.00$0.150
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%
Avg Response Time19.74s
Defect Detection
66.7%(10/15)
Document Understanding
88.9%(8/9)
Object Counting
0%(0/10)
Object Understanding
64.3%(9/14)
Spatial Understanding
57.9%(11/19)