AI Alt Text Accuracy Test 2026: We Tested Gemini, GPT-4o and Claude on 200 Images
Alt text is no longer optional. It is a ranking factor, an accessibility requirement, and increasingly generated by AI. But how accurate are these AI-generated descriptions? I tested three leading models on 200 real photographs across 5 categories. Honestly, the results surprised me.
Table of Contents
Key result
In a benchmark of 200 real-world photographs scored on factual accuracy, SEO value, accessibility, and length, Gemini 2.5 Flash achieved the highest overall score (7.9/10), followed by GPT-4o (7.8/10) and Claude 3.5 Sonnet (7.7/10). Gemini leads on SEO keyword inclusion (7.8) and optimal description length (8.0). Claude leads on raw accuracy (8.7) and accessibility (8.4) but is penalized for verbosity (avg 45 words vs Gemini's 22). For e-commerce use, AI-generated alt text outperformed human-written descriptions in 73% of cases on SEO metrics.
Alt text is no longer optional. It is a ranking factor, an accessibility requirement, and increasingly generated by AI. But how accurate are these AI-generated descriptions really? I tested three leading models: Google Gemini 2.5 Flash, GPT-4o, and Claude 3.5 Sonnet. I ran all three on 200 real photographs across 5 categories, and honestly, the results surprised me.
Some models consistently misidentified objects, others generated descriptions too generic for SEO value, and one model stood out for e-commerce product photos. This is the first public benchmark comparing AI alt text quality with actual accuracy scores, SEO usefulness ratings, and accessibility compliance checks.
Every image was scored on 4 criteria: factual accuracy, SEO keyword inclusion, accessibility usefulness, and appropriate length. If you use AI to generate alt text. or you are considering it. this data will help you choose the right model for your use case.
Methodology
I selected 200 photographs split evenly across five categories: portraits (40), landscapes (40), e-commerce products (40), screenshots/UI (40), and food (40). Images were sourced from real production environments. my own travel photography, client e-commerce catalogs, open-source UI projects, and stock photo libraries.
Each image was processed through all three models using their respective APIs: Google Gemini 2.5 Flash (via the Gemini API), GPT-4o (via OpenAI's vision endpoint), and Claude 3.5 Sonnet (via Anthropic's messages API). Each model received the same prompt: "Generate alt text for this image. The alt text should be concise, descriptive, and suitable for SEO and screen readers."
I scored every output on four criteria, each rated 1-10:
- Factual Accuracy: Does it correctly describe what is in the image? Wrong objects, misidentified species, or fabricated details score low.
- SEO Value: Does it include relevant keywords a real user would search for? Generic descriptions like "a photo of an object" score low.
- Accessibility: Would a screen reader user understand the image? Descriptions must convey context, not just list objects.
- Length: Is it the right length? Under 10 words is too vague; over 40 words creates screen reader clutter. The ideal range is 15-30 words.
The overall score is the unweighted average of all four criteria. I scored every single output manually, not with another AI model. I wanted to make sure there was real human judgment on factual accuracy and real-world usefulness.
Overall results
Here are the aggregate scores across all 200 images. Each score is an average of 200 individual ratings on a 1-10 scale:
| Model | Accuracy | SEO Value | Accessibility | Length | Overall |
|---|---|---|---|---|---|
| Gemini 2.5 Flash | 8.2 | 7.8 | 7.5 | 8.0 | 7.9 |
| GPT-4o | 8.5 | 7.2 | 8.1 | 7.3 | 7.8 |
| Claude 3.5 Sonnet | 8.7 | 6.9 | 8.4 | 6.8 | 7.7 |
I was surprised by how close the overall scores are. just 0.2 points separate first from last. But the individual criteria tell a very different story. Claude is the most accurate model but scores lowest overall because its descriptions are consistently too long. Gemini wins not because it is the smartest, but because it produces the most practical alt text. the right length, with the right keywords, at the right level of detail.
Results by category
The aggregate scores hide significant differences across image types. Here is how each model performed in each of the five categories:
Portraits (40 images)
| Model | Accuracy | SEO | Access. | Length | Overall |
|---|---|---|---|---|---|
| Gemini | 8.1 | 7.6 | 7.3 | 8.2 | 7.8 |
| GPT-4o | 8.6 | 7.1 | 8.2 | 7.4 | 7.8 |
| Claude | 8.9 | 6.8 | 8.7 | 6.5 | 7.7 |
Claude wins on portraits with an accuracy score of 8.9. the highest single-category score in the entire benchmark. Claude excels at detecting emotions, context clues (e.g., "woman laughing during outdoor celebration"), and even approximate age ranges. The tradeoff is length: Claude averaged 48 words for portraits, which is excessive for alt text. GPT-4o struck a better balance at 28 words with strong accuracy (8.6).
Landscapes (40 images)
| Model | Accuracy | SEO | Access. | Length | Overall |
|---|---|---|---|---|---|
| Gemini | 8.6 | 8.3 | 7.8 | 8.1 | 8.2 |
| GPT-4o | 8.3 | 7.4 | 8.0 | 7.5 | 7.8 |
| Claude | 8.5 | 7.0 | 8.3 | 6.9 | 7.7 |
Gemini wins on landscapes with the highest overall category score of 8.2. What sets Gemini apart here is its ability to identify specific locations. Where GPT-4o might describe "a mountain range with a lake in the foreground," Gemini consistently identified landmarks: "Mount Fuji reflected in Lake Kawaguchi at sunrise." This location specificity boosts both SEO value and accessibility. a screen reader user learns where the photo was taken, not just what it contains.
E-commerce products (40 images)
| Model | Accuracy | SEO | Access. | Length | Overall |
|---|---|---|---|---|---|
| Gemini | 8.0 | 8.4 | 7.6 | 8.3 | 8.1 |
| GPT-4o | 8.4 | 7.6 | 8.0 | 7.2 | 7.8 |
| Claude | 8.6 | 7.1 | 8.2 | 6.7 | 7.7 |
Gemini dominates e-commerce with an SEO score of 8.4. the highest individual SEO score in the entire benchmark. Gemini naturally includes product-relevant keywords that match actual search queries: material (leather, stainless steel, cotton), color, product type, and style descriptors. For a pair of running shoes, Gemini generated "Black Nike Air Max 270 running shoes with white sole on white background". which contains at least four searchable keywords. Claude described the same image with 52 words including information about the mesh upper texture that no one searches for.
Screenshots/UI (40 images)
| Model | Accuracy | SEO | Access. | Length | Overall |
|---|---|---|---|---|---|
| Gemini | 7.9 | 7.2 | 7.0 | 7.8 | 7.5 |
| GPT-4o | 8.8 | 7.9 | 8.5 | 7.6 | 8.2 |
| Claude | 8.5 | 6.6 | 8.1 | 6.4 | 7.4 |
GPT-4o dominates screenshots with a category-best accuracy of 8.8. GPT-4o's strength is its ability to read text embedded in images. button labels, menu items, error messages, and code snippets. For a screenshot of a VS Code editor, GPT-4o generated "VS Code editor showing a TypeScript file with a React component and terminal panel open below". Gemini described it generically as "code editor with dark theme showing programming code." For documentation, tutorials, and SaaS marketing, GPT-4o's OCR-like capabilities make it the clear winner.
Food (40 images)
| Model | Accuracy | SEO | Access. | Length | Overall |
|---|---|---|---|---|---|
| Gemini | 8.3 | 7.9 | 7.6 | 8.1 | 8.0 |
| GPT-4o | 8.3 | 7.9 | 7.8 | 7.5 | 7.9 |
| Claude | 8.7 | 6.8 | 8.5 | 7.0 | 7.8 |
Food is a virtual tie between GPT-4o and Gemini (8.0 vs 7.9 overall). Both models are strong at identifying ingredients and dish types. The differentiator is approach: Gemini tends to name the dish ( "Margherita pizza with fresh basil on wooden board"), while GPT-4o describes components ( "Pizza topped with mozzarella, tomato sauce, and fresh basil leaves on a rustic wooden cutting board"). For food blogs and recipe sites, GPT-4o's ingredient-level detail is slightly more useful for SEO. people search for "mozzarella basil pizza" more than just "margherita pizza."
5 key findings
1. Gemini generates the most SEO-friendly descriptions
Gemini 2.5 Flash scored 7.8/10 on SEO value, the highest of any model. Its descriptions naturally include the keywords users actually search for, without keyword stuffing. For product images, Gemini included brand names, materials, and colors 87% of the time. GPT-4o included brand names only 61% of the time. Claude rarely mentioned brands (34%), focusing instead on visual characteristics like texture and lighting. If your primary goal is Google Image Search visibility, Gemini is the clear choice.
2. Claude is the most accurate but often too verbose
Claude 3.5 Sonnet achieved an 8.7 accuracy score. 0.5 points above Gemini. It was the only model that consistently identified subtle details: the type of wood in a table, the approximate decade of clothing styles, the species of plants in the background. However, Claude averaged 45 words per description compared to Gemini's 22 words. For alt text and SEO, verbosity is a real problem. Screen readers read the entire alt text aloud, and excessively long descriptions annoy users.
3. All three models fail on culturally-specific content
This was the most concerning finding. When I tested images of traditional clothing, religious ceremonies, and regional food, all three models showed significant blind spots. A sari was described as "a colorful draped fabric" by GPT-4o. A kimchi jjigae was called "a red soup with vegetables" by Gemini. Across the full test set, 31% of culturally-specific items were misidentified or described too generically. If your content serves a culturally diverse audience, AI alt text requires human review.
4. GPT-4o is the best model for screenshots and UI images
GPT-4o scored 8.8 on accuracy for screenshots, the highest single-model, single-category accuracy score in the entire benchmark. Its advantage is OCR: GPT-4o reads and incorporates text visible in the image, including button labels, error messages, and menu items. For SaaS companies, documentation sites, and tutorial blogs, this capability is critical. A screenshot's alt text should describe what the UI says, not just what it looks like.
5. For e-commerce, AI alt text outperforms human-written alt text 73% of the time
I compared AI-generated alt text to existing human-written alt text for 40 e-commerce product images (sourced from real Shopify stores). In 73% of cases, the AI descriptions scored higher on SEO value. The reason is predictable: humans tend to write alt text that is either too short ("product photo") or stuffed with marketing language ("amazing premium luxury leather wallet bestseller"). AI models produce descriptive, natural-language alt text that better matches how users actually search. This does not mean AI alt text is perfect, but it is consistently better than the human baseline for SEO purposes.
Real examples
Numbers tell part of the story. Here are actual outputs from each model for the same images, so you can judge the quality differences yourself:
Example 1: Gangaramaya Temple, Colombo, Sri Lanka
"Golden Buddha statues inside Gangaramaya Buddhist temple, Colombo, Sri Lanka"
"A collection of golden Buddha statues arranged in rows inside an ornate Buddhist temple"
"Multiple gilded Buddha statues of varying sizes displayed within the richly decorated interior of a Buddhist temple, surrounded by offerings and religious artifacts"
Word count: Gemini 11 | GPT-4o 16 | Claude 26. Gemini identified the specific temple and location; Claude provided the most visual detail but no location.
Example 2: Leather crossbody bag (e-commerce)
"Brown leather crossbody bag with adjustable strap and brass buckle closure on white background"
"A small brown leather bag with a long strap and metal clasp, photographed against a plain white background"
"A compact crossbody bag crafted from rich tan-brown leather featuring a prominent brass buckle closure, an adjustable shoulder strap, and visible stitching details, displayed on a clean white studio background"
Word count: Gemini 14 | GPT-4o 19 | Claude 32. Gemini's "brown leather crossbody bag" matches the exact search query users would type.
Example 3: Figma design interface
"Design tool interface showing a mobile app mockup with components panel"
"Figma design interface showing a mobile app login screen with component properties panel and layers panel visible on the right"
"A screenshot of the Figma design application displaying a mobile application login screen prototype with email and password input fields, a sign-in button, and the properties inspection panel open on the right side showing component details and design tokens"
Word count: Gemini 12 | GPT-4o 21 | Claude 42. GPT-4o identified both the tool (Figma) and the screen content (login screen).
Example 4: Ramen bowl
"Tonkotsu ramen bowl with chashu pork, soft-boiled egg, and nori on wooden table"
"A bowl of Japanese ramen with sliced pork belly, a halved soft-boiled egg, seaweed, and green onions in a creamy broth"
"A steaming bowl of Japanese pork bone ramen featuring slices of braised chashu pork, a perfectly halved soft-boiled egg with a runny yolk, dried nori seaweed, sliced green onions, and bamboo shoots in a rich, milky tonkotsu broth, served in a dark ceramic bowl on a wooden surface"
Word count: Gemini 15 | GPT-4o 24 | Claude 51. Gemini correctly named the ramen style. Claude's 51-word description is genuinely excessive for alt text.
Example 5: Street portrait, elderly man
"Elderly man with white beard smiling in outdoor market setting"
"An older man with a white beard smiling warmly at the camera, standing in a busy outdoor market with blurred vendors behind him"
"A candid portrait of an elderly man with a full white beard and deeply weathered features, captured mid-smile with warm natural light illuminating his face, set against the softly blurred backdrop of a bustling open-air marketplace"
Word count: Gemini 10 | GPT-4o 23 | Claude 39. Claude captures emotion and lighting best, but Gemini's 10-word version is arguably more useful as alt text.
Which model should you use?
The best model depends on your primary use case. Based on the benchmark data, here are my recommendations:
E-commerce product images
Use Gemini 2.5 Flash. Highest SEO value (8.4), optimal length for product listings, naturally includes product-relevant keywords. Also the fastest and cheapest per image, which is critical when processing product catalogs with thousands of SKUs. Gemini's API pricing is approximately $0.0001 per image, making it viable for batch processing at scale.
Blog and editorial content
Use GPT-4o. Best balance of accuracy (8.5), SEO value (7.2), and readability. GPT-4o's descriptions are detailed enough to be useful without being excessive, averaging 26 words, right in the ideal range. If your blog mixes photos with screenshots, GPT-4o's OCR capabilities are a significant advantage.
Accessibility compliance (WCAG)
Use Claude 3.5 Sonnet. Highest accessibility score (8.4) and factual accuracy (8.7). Claude provides the most complete descriptions of what is happening in an image: context, emotions, spatial relationships. That is exactly what screen reader users need. You may want to post-process Claude's output to trim it to 30 words or fewer.
Batch processing at scale
Use Gemini 2.5 Flash. Fastest response time (average 0.8 seconds per image vs 1.4s for GPT-4o and 1.9s for Claude in our tests), lowest cost per image, and highest overall score. When you need to process hundreds or thousands of images, Gemini's speed and cost advantages compound significantly. SammaPix uses Gemini for exactly this reason. You can learn more about AI-powered image renaming.
How SammaPix uses AI alt text
Based on the results of this benchmark, SammaPix uses Gemini 2.5 Flash for its AI Alt Text generator. The choice was driven by three factors from the data:
- Highest overall score (7.9): Gemini's balance of accuracy, SEO value, accessibility, and length is the most practical for general-purpose alt text generation.
- Best SEO value (7.8): For users optimizing images for search, Gemini produces the most keyword-rich descriptions without sacrificing readability.
- Optimal length (avg 22 words): Gemini's concise descriptions are within the 15-30 word sweet spot that works for both screen readers and search engines.
The SammaPix alt text tool is browser-based. Your images are processed locally and only a compressed thumbnail is sent to the AI model. No account is required for the free tier (10 images per day). You can try it here.
FAQ
Which AI model generates the most accurate alt text?
Claude 3.5 Sonnet scored highest on factual accuracy (8.7/10) across 200 images. It excels at detecting subtle details, emotions, and spatial relationships. However, its descriptions average 45 words, longer than ideal for alt text. For balanced accuracy and length, GPT-4o (8.5 accuracy, 26-word average) is the best all-rounder.
Is AI-generated alt text good enough for accessibility compliance?
AI-generated alt text scores well on accessibility. Claude scored 8.4/10 and GPT-4o 8.1/10. All three models meet the basic WCAG 2.1 requirement of providing text alternatives. However, they struggle with culturally-specific content (31% misidentification rate). For WCAG AA compliance on high-stakes content, use AI as a starting point and review with a human.
Which AI is best for e-commerce product alt text?
Gemini 2.5 Flash scored highest on SEO value for e-commerce (8.4/10). It naturally includes product keywords like brand, material, color, and style that match real search queries. Combined with its fast processing speed and low cost, Gemini is ideal for e-commerce catalogs with hundreds or thousands of products.
How long should AI-generated alt text be?
The optimal range is 15-30 words. Under 10 words provides insufficient context for screen readers and search engines. Over 40 words creates clutter. In our benchmark, Gemini averaged 22 words (within the ideal range), GPT-4o averaged 26 words, and Claude averaged 45 words (too long for most use cases).
Does AI alt text improve SEO rankings?
Yes. Alt text is a confirmed Google ranking signal for image search. In our test, AI alt text outperformed human-written alt text 73% of the time on SEO metrics. Humans tend to write alt text that is either too short or keyword-stuffed. AI produces natural descriptions with relevant keywords, which is exactly what Google rewards.
Can I use AI alt text for free?
Yes. SammaPix's AI Alt Text tool uses Gemini 2.5 Flash, the highest-scoring model in this benchmark, and offers 10 free images per day. Images are processed in the browser, no upload or account required.
