Claude Opus 4.8 vs Gemini 4 Carbon
Gemini 4 Carbon and Claude Opus 4.8 score 89.4% vs 58.3% averaged across five Vision Evals tasks (#1 and #43 of 68 models), so Gemini 4 Carbon leads overall.
- Gemini 4 Carbon wins all 5 tasks, with its widest lead on object detection (84.5% vs 38.6%).
- Gemini 4 Carbon is about a quarter of the cost: $0.0061 vs $0.021 overall average cost per sample.
- Claude Opus 4.8 is faster: 7.7s vs 8.7s per sample.
Roboflow Vision Evals. Full breakdown below.
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Claude Opus 4.8 vs Gemini 4 Carbon on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Opus 4.8 vs Gemini 4 Carbon Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Opus 4.8 | Gemini 4 Carbon |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | May 2026 | Nov 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | No published price |
| Output $/1M | $25.00 | No published price |
| Vision Tasks | ||
| Promptable Concept Segmentation | Not listed | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 58.3% | 89.4% |
| Avg cost / sample | $0.021 | $0.0061 |
| Avg speed / sample | 7.66s | 8.71s |
| By task | ||
| Object Detection (low) | 38.6% | 84.5% ±0.3, Mean of 3 runs, range 84.2 to 84.8 |
| Object Detection (high) | – | 85.9% ±0.3, Mean of 3 runs, range 85.6 to 86.2 |
| Counting (low) | 54.0% | 90.1% ±1.4, Mean of 3 runs, range 89.2 to 91.9 |
| Counting (high) | – | 86.9% ±2.7, Mean of 3 runs, range 83.8 to 89.2 |
| Identification (low) | 84.4% | 93.8% ±0.0, Mean of 3 runs, range 93.8 to 93.8 |
| Identification (high) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 61.5% | 87.2% |
| by category |
|
|
| OCR (high) | 62.1% | 89.7% |
| by category |
|
|
| Reasoning (low) | 53.0% | 91.4% ±1.7, Mean of 3 runs, range 90.1 to 93.4 |
| Reasoning (high) | 52.3% | 92.3% ±0.3, Mean of 3 runs, range 92.0 to 92.7 |
Claude Opus 4.8 vs Gemini 4 Carbon: 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. 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 4 Carbon is a multimodal model from Google. It builds on Gemini 4 Argon and supports reasoning over text and images. Google describes improvements in coding and long-running tasks. Model weights are not publicly released.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 4 Carbon performed better. It scores higher on all five vision tasks and averages 89.4% (#1 of 68) against 58.3% (#43 of 68) 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 at low effort, Gemini 4 Carbon leads with 84.5% against 38.6%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 4 Carbon is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0061 per sample against $0.021. Actual costs depend on your image sizes, prompts, and output length.
Claude Opus 4.8 is faster. Across Roboflow's Vision Evals it averaged 7.7s per inference against 8.7s. 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.