Claude Opus 4.6 vs Gemma 3 4B
Compare Claude Opus 4.6 and Gemma 3 4B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
Compare Claude Opus 4.6 vs Gemma 3 4B live
Run the same image across every model that supports a task and compare their outputs side-by-side.
Extract and compare text from images across multiple models.
Upload an image
Drag and drop an image here, or click to browse
Models in this comparison
Claude Opus 4.6 vs Gemma 3 4B: 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 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 4.6 vs Gemma 3 4B Comparison Table
| Property | Claude Opus 4.6 | Gemma 3 4B |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Mar 2025 |
| Context Window | 1.0M | 128K |
| Parameters | 4B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $0.050 |
| Output $/1M | $25.00 | $0.100 |
| 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% | 37.31% |
| Avg Response Time | 23.35s | 16.80s |
| Median input tokensincl. image tokens | 2.2K | |
| Median output tokens | 130 | |
| Est. cost / taskon this benchmark | $0.014 | |
| Defect Detection | 73.3%(11/15) | 60%(9/15) |
| Document Understanding | 77.8%(7/9) | 55.6%(5/9) |
| Object Counting | 20%(2/10) | 0%(0/10) |
| Object Understanding | 71.4%(10/14) | 42.9%(6/14) |
| Spatial Understanding | 68.4%(13/19) | 26.3%(5/19) |
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