Claude Opus 4 vs Gemma 4 12B
Compare Claude Opus 4 and Gemma 4 12B side-by-side.
Compare Claude Opus 4 vs Gemma 4 12B live
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These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
Claude Opus 4 vs Gemma 4 12B: Overview
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 4 12B is an open-weight multimodal model from Google in the Gemma 4 family. It is intended for text and image understanding tasks such as visual question answering, OCR, captioning, and document understanding, with a smaller parameter footprint than the larger Gemma 4 variants.
This entry is connected to Roboflow Playground vision evals for comparison. No runnable Playground workflow is configured yet, so the model page is used for discovery and benchmark context rather than direct hosted inference.
Claude Opus 4 vs Gemma 4 12B Comparison Table
| Property | Claude Opus 4 | Gemma 4 12B |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | May 2025 | Jun 2026 |
| Context Window | 200K | — |
| Parameters | 12B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $15.00 | |
| Output $/1M | $75.00 | |
| Vision Tasks | ||
| Captioning | ||
| OCR | ||
| Vision Language | ||
| Visual Question Answering | ||
| 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% | 62.69% |
| Avg Response Time | 19.74s | 6.88s |
| Defect Detection | 66.7%(10/15) | 73.3%(11/15) |
| Document Understanding | 88.9%(8/9) | 88.9%(8/9) |
| Object Counting | 0%(0/10) | 10%(1/10) |
| Object Understanding | 64.3%(9/14) | 78.6%(11/14) |
| Spatial Understanding | 57.9%(11/19) | 57.9%(11/19) |