Claude Opus 4.8 vs Gemini 3.1 Pro
Compare Claude Opus 4.8 and Gemini 3.1 Pro side-by-side. See how these vision models stack up in Image Captioning, Classification, OCR, Object Detection, and Open Prompt.
Compare Claude Opus 4.8 vs Gemini 3.1 Pro live
Run the same image across every model that supports a task and compare their outputs side-by-side.
Detect and compare bounding boxes across models on the same image.
Upload an image
Drag and drop an image here, or click to browse
Models in this comparison
Claude Opus 4.8 vs Gemini 3.1 Pro on Vision Evals
Gemini 3.1 Pro scores higher on 5 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.1 Pro leads 56.9% to 18.6%.
Overall, Claude Opus 4.8 averages 64.8% (#15 of 16) against 84.6% (#2 of 16) for Gemini 3.1 Pro.
Gemini 3.1 Pro is cheaper ($0.0068 vs $0.013 per sample), while Claude Opus 4.8 is faster (4.2s vs 5.9s per sample).
Claude Opus 4.8 vs Gemini 3.1 Pro Comparison Table
Evals updated July 10, 2026Pricing updated July 21, 2026
| Property | Claude Opus 4.8 | Gemini 3.1 Pro |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Feb 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $2.00 |
| Output $/1M | $25.00 | $12.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks | ||
| Overall | 64.8% | 84.6% |
| Object Detection | 18.6% | 56.9% |
| Counting | 52.7% | 71.6% |
| Identification | 75.0% | 100.0% |
| OCR | 93.8% | 92.6% |
| Data Extraction | 87.6% | 94.8% |
| Reasoning | 60.9% | 91.3% |
| Avg cost / sample | $0.013 | $0.0068 |
| Avg speed / sample | 4.2s | 5.9s |
Claude Opus 4.8 vs Gemini 3.1 Pro: Overview
Claude Opus 4.8 is Anthropic's most capable generally available large language model, released on May 28, 2026 as an incremental upgrade to Claude Opus 4.7. The model accepts text and image inputs and produces text outputs, with a 1 million token context window on the Claude API, Amazon Bedrock, and Google Cloud Vertex AI (200k tokens on Microsoft Foundry) and up to 128k max output tokens. It uses adaptive thinking and supports adjustable effort tiers — high by default, with extra and max tiers available for more demanding tasks. A fast mode operates at approximately 2.5x standard speed. The model is described by Anthropic as a hybrid reasoning model designed for advanced coding, agentic workflows, long-context reasoning, and professional knowledge work.
Key behavioral improvements over Opus 4.7 include substantially reduced rates of unreported code flaws, improved honesty in self-assessment, and better tool-calling reliability. On Anthropic's Super-Agent benchmark, Opus 4.8 completes every case end-to-end, and it scores 84% on Online-Mind2Web for computer-use and browser-agent tasks. It achieves 88.6% on SWE-bench Verified and 69.2% on SWE-bench Pro. Alongside the model, Anthropic launched Dynamic Workflows in Claude Code (research preview), which enables Claude to orchestrate hundreds of parallel subagents for codebase-scale tasks such as large migrations. The Messages API was also updated to accept mid-task system messages without breaking prompt caching, improving support for long-running agentic pipelines.
Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on 5 of the six vision tasks and averages 84.6% (#2 of 16) against 64.8% (#15 of 16) for Claude Opus 4.8. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark, Gemini 3.1 Pro leads with 56.9% against 18.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.1 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0068 per sample against $0.013. Claude Opus 4.8 is priced at $5.00 per 1M input tokens and $25.00 per 1M output; Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Opus 4.8 is faster. Across Roboflow's Vision Evals it averaged 4.2s per inference against 5.9s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.