Claude Opus 4.6 vs Gemini 3.7 Flash
Gemini 3.7 Flash: 80.1% average across five Vision Evals tasks (#10 of 69 models). We have not run Claude Opus 4.6 through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
Compare Claude Opus 4.6 vs Gemini 3.7 Flash 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
Claude Opus 4.6 vs Gemini 3.7 Flash Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | Claude Opus 4.6 | Gemini 3.7 Flash |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Aug 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Undisclosed |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $0.750 |
| Output $/1M | $25.00 | $3.75 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 80.1% |
| Avg cost / sample | – | $0.0033 |
| Avg speed / sample | – | 11.04s |
| By task | ||
| Object Detection (low) | – | 70.5% ±1.1, Mean of 3 runs, range 69.4 to 71.5 |
| Object Detection (high) | – | 74.3% ±0.8, Mean of 3 runs, range 73.3 to 75.0 |
| Counting (low) | – | 78.4% ±1.4, Mean of 3 runs, range 77.0 to 79.7 |
| Counting (high) | – | 79.3% ±2.0, Mean of 3 runs, range 77.0 to 81.1 |
| Identification (low) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | – | 73.9% |
| by category |
| |
| OCR (high) | – | 78.8% |
| by category |
| |
| Reasoning (low) | – | 80.8% ±2.0, Mean of 3 runs, range 78.8 to 82.8 |
| Reasoning (high) | – | 81.9% ±1.3, Mean of 3 runs, range 80.1 to 82.8 |
Claude Opus 4.6 vs Gemini 3.7 Flash: 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.
Gemini 3.7 Flash is a proprietary multimodal model from Google, positioned in the Flash branch of the Gemini 3 series that trades some of the capacity of the larger Pro models for lower latency and lower cost per token. It accepts interleaved text and image input alongside other modalities handled by the Gemini family and returns text, and it continues the series pattern of exposing a configurable thinking budget so that reasoning effort can be scaled up for harder problems or reduced for high throughput extraction, routing and classification work. The model is announced roughly three weeks after Gemini 3.6 Flash, part of an unusually fast iteration cadence within the Flash line.
Google reports gains concentrated in agentic coding and front end generation, citing a WebDev Arena Elo of 1588 for this release compared with 1538 for the preceding Flash model, and describes it as producing more functional layouts and more feature complete applications in fewer prompts. Weights are not published and the architecture, parameter count and training corpus are undisclosed, consistent with prior Gemini releases. Visual capability follows the Flash lineage, covering image and document understanding, chart and diagram interpretation, text recognition in images, and general visual question answering.