Claude Sonnet 5 vs Gemini 4 Carbon
Gemini 4 Carbon and Claude Sonnet 5 score 89.4% vs 55.3% averaged across five Vision Evals tasks (#1 and #52 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 36.1%).
- Gemini 4 Carbon is cheaper: $0.0061 vs $0.0074 overall average cost per sample.
- Claude Sonnet 5 is faster: 5.9s vs 8.7s per sample.
Roboflow Vision Evals. Full breakdown below.
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Claude Sonnet 5 vs Gemini 4 Carbon on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Sonnet 5 vs Gemini 4 Carbon Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Sonnet 5 | Gemini 4 Carbon |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 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 | $2.00 | No published price |
| Output $/1M | $10.00 | 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 | 55.3% | 89.4% |
| Avg cost / sample | $0.0074 | $0.0061 |
| Avg speed / sample | 5.86s | 8.71s |
| By task | ||
| Object Detection (low) | 36.1% | 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) | 56.8% | 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) | 81.3% | 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) | 59.4% | 87.2% |
| by category |
|
|
| OCR (high) | 59.5% | 89.7% |
| by category |
|
|
| Reasoning (low) | 43.0% | 91.4% ±1.7, Mean of 3 runs, range 90.1 to 93.4 |
| Reasoning (high) | 43.0% | 92.3% ±0.3, Mean of 3 runs, range 92.0 to 92.7 |
Claude Sonnet 5 vs Gemini 4 Carbon: Overview
Claude Sonnet 5 is a mid-tier large language model from Anthropic, released on June 30, 2026, as the latest model in the Sonnet series and a direct successor to Claude Sonnet 4.6. It is a hybrid reasoning model designed primarily for agentic workflows, software coding, and professional tasks. The model features a 1 million token context window, a 128k maximum output token limit, and runs adaptive thinking by default, giving API users fine-grained control over reasoning effort across five levels (low, medium, high, max, and extra-high). It uses an updated tokenizer shared with Opus 4.7 and later models, which produces approximately 30% more tokens for equivalent text compared to earlier Claude models.
The model supports text and image input with text output, and accepts tools including browsers and terminals for autonomous multi-step task execution. Anthropic's safety evaluations report that Sonnet 5 shows a lower rate of undesirable behaviors than Sonnet 4.6 and is generally safer in agentic contexts, with improved resistance to prompt injection and reduced sycophancy. Cybersecurity safeguards equivalent to those on Opus 4.7 and 4.8 are active, though Anthropic notes the model was not deliberately trained on cybersecurity tasks. The model is proprietary and API-only, with no open weights.
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 55.3% (#52 of 68) for Claude Sonnet 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 4 Carbon leads with 84.5% against 36.1%. 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 $0.0074. Actual costs depend on your image sizes, prompts, and output length.
Claude Sonnet 5 is faster. Across Roboflow's Vision Evals it averaged 5.9s 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 object detection and open prompts in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.