Claude Opus 5 vs Gemini 3.8 Flash
Compare Claude Opus 5 and Gemini 3.8 Flash side-by-side. See how these vision models stack up in Image Captioning, OCR, Open Prompt, Object Detection, and Classification.
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Models in this comparison
Claude Opus 5 vs Gemini 3.8 Flash on Vision Evals
Gemini 3.8 Flash scores higher on 5 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.8 Flash leads 68.1% to 54.4%.
Overall, Claude Opus 5 averages 78.3% (#11 of 36) against 85.1% (#3 of 36) for Gemini 3.8 Flash.
Gemini 3.8 Flash is cheaper ($0.0033 vs $0.017 per sample), while Claude Opus 5 is faster (7.4s vs 11.6s per sample).
Claude Opus 5 vs Gemini 3.8 Flash Comparison Table
Evals updated September 2, 2026Pricing updated September 2, 2026
| Property | Claude Opus 5 | Gemini 3.8 Flash |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | |
| Output $/1M | $25.00 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Image Tagging | ||
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 78.3% | 85.1% |
| Avg cost / sample | $0.017 | $0.0033 |
| Avg speed / sample | 7.38s | 11.65s |
| By task | ||
| Object Detection (low) | 54.4% | 68.1% ±0.8, Mean of 3 runs, range 67.3 to 69.0 |
| Object Detection (high) | – | 74.8% ±1.1, Mean of 3 runs, range 73.4 to 75.6 |
| Counting (low) | 70.3% | 78.8% ±2.7, Mean of 3 runs, range 75.7 to 81.1 |
| Counting (high) | – | 79.3% ±1.4, Mean of 3 runs, range 78.4 to 81.1 |
| Identification (low) | 90.6% | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| Identification (high) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 93.2% | 87.3% ±0.8, Mean of 3 runs, range 86.5 to 88.2 |
| OCR (high) | – | 88.8% ±0.7, Mean of 3 runs, range 88.0 to 89.4 |
| Data Extraction (low) | 89.7% | 97.3% ±0.5, Mean of 3 runs, range 96.9 to 97.9 |
| Data Extraction (high) | – | 94.8% ±1.0, Mean of 3 runs, range 93.8 to 95.9 |
| Reasoning (low) | 71.5% | 81.2% ±0.3, Mean of 3 runs, range 80.8 to 81.5 |
| Reasoning (high) | 74.2% | 84.5% ±1.0, Mean of 3 runs, range 83.4 to 85.4 |
Claude Opus 5 vs Gemini 3.8 Flash: Overview
Claude Opus 5 is a large language model with multimodal vision capabilities developed by Anthropic, released on July 24, 2026 as the fourth model in the Claude 5 family. It sits in the Opus tier of Anthropic's lineup, positioned below the Mythos-class Fable 5 and Mythos 5 models, and is framed by Anthropic as the go-to model for most knowledge work and automation tasks. The model approaches Fable 5's capabilities at roughly half the cost, priced at $5 per million input tokens and $25 per million output tokens. It becomes the default model on Claude Max and the strongest model available on Claude Pro. The model ships with a 1 million token context window and an adjustable "effort" parameter that allows users to trade reasoning depth for speed and token savings. Early enterprise customers reported that Opus 5 achieved comparable performance to Opus 4.8's maximum-reasoning mode while generating significantly fewer tokens on average, and demonstrated higher accuracy on financial modeling tasks with fewer tool calls and less time.
Claude Opus 5 supports multimodal inputs including images and text, and is designed for agentic workflows, coding, scientific research, and complex enterprise tasks. Anthropic reports the model scores 10.2 percentage points higher than Opus 4.8 on an internal chemistry benchmark, making it the most capable generally available model for scientific research in the Claude lineup. Cyber classifiers on Opus 5 are designed to intervene approximately 85 percent less often than those on Fable 5, with fallback to Opus 4.8 when a classifier triggers. The model does not retain user data for 30 days, unlike Fable 5. It is available across Anthropic's platforms including Claude Code and Claude Cowork, as well as cloud partners.
Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.
On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.8 Flash performed better. It scores higher on 5 of the six vision tasks and averages 85.1% (#3 of 36) against 78.3% (#11 of 36) for Claude Opus 5. 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 at low effort, Gemini 3.8 Flash leads with 68.1% against 54.4%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.8 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0033 per sample against $0.017. Actual costs depend on your image sizes, prompts, and output length.
Claude Opus 5 is faster. Across Roboflow's Vision Evals it averaged 7.4s per inference against 11.6s. 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 OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.