Claude Opus 4.1 vs Gemma 3 4B
Compare Claude Opus 4.1 and Gemma 3 4B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Claude Opus 4.1 vs Gemma 3 4B: Overview
Claude 4.1 Opus, released by Anthropic in August 2025, is the upgraded flagship of the Claude 4 family, building on Opus 4 with stronger reasoning and agentic capabilities. Like its predecessor, it is multimodal and optimized for text, code, and tool use, with support for large context windows suited to multi-file codebases, technical workflows, and long-horizon problem solving.
On benchmarks, Opus 4.1 improves coding performance, reaching ~74.5% on SWE-Bench Verified compared to Opus 4’s ~72.5%. It demonstrates more precise debugging, refactoring, and orchestration of agentic tasks while maintaining similar safety and alignment safeguards. It is best suited for enterprise-scale software development, research automation, and advanced reasoning workflows where reliability and depth of analysis are critical.
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 4.1 vs Gemma 3 4B Comparison Table
| Property | Claude Opus 4.1 | Gemma 3 4B |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Aug 2025 | Mar 2025 |
| Context Window | 200K | 128K |
| Parameters | 4B | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $15.00 | $0.050 |
| Output $/1M | $75.00 | $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 | 59.7% | 37.31% |
| Avg Response Time | 7.09s | 16.80s |
| Median input tokensincl. image tokens | 2.0K | |
| Median output tokens | 140 | |
| Est. cost / taskon this benchmark | $0.040 | |
| Defect Detection | 73.3%(11/15) | 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 | 63.2%(12/19) | 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