Claude Opus 4.6 vs Gemma 3 12B
Compare Claude Opus 4.6 and Gemma 3 12B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Claude Opus 4.6 vs Gemma 3 12B: Overview
Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.
As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.
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 4.6 vs Gemma 3 12B Comparison Table
| Property | Claude Opus 4.6 | Gemma 3 12B |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Mar 2025 |
| Context Window | 1.0M | 128K |
| Parameters | 12B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $0.050 |
| Output $/1M | $25.00 | $0.150 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| Object Detection | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 64.18% | |
| Avg Response Time | 23.35s | |
| Median input tokensincl. image tokens | 2.2K | |
| Median output tokens | 130 | |
| Est. cost / taskon this benchmark | $0.014 | |
| Defect Detection | 73.3%(11/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 20%(2/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 68.4%(13/19) | |
Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology