A model for every idea
Explore AI models for research, writing, image editing and video generation. Compare measured performance and task costs to find a model for your work.
18 models
Research and writing
12- Claude Fable 5.1Entrega extractos de investigación, código, registros o diagramas de flujo a Claude Fable 5.1 para organizar la evidencia, analizar posibles causas y desglosar problemas complejos en planes accionables.
- Claude Haiku 5.5Proporciona a Claude Haiku 5.5 un pasaje, un conjunto de entradas breves o una pregunta específica. Convierte el material en un resumen conciso, un conjunto útil de categorías o una lista de detalles que puedas verificar contra la fuente.
- Claude Opus 4.6Usa Claude Opus 4.6 para examinar material fuente sustancial, razonar sobre cambios difíciles y dar forma a un borrador con cuidado. Aporta el contexto y el resultado deseado, luego perfecciona el trabajo mediante la conversación.
- Claude Opus 5.5Convierte ideas y materiales fuente en resultados de trabajo utilizables. Desarrolla artículos, razona decisiones, construye páginas web o explora el movimiento en código, y luego perfecciona los resultados en la conversación.
- Claude Sonnet 5.5Comienza con un objetivo claro y el material detrás de él. Usa Claude Sonnet 5.5 para desarrollar un documento estructurado, discutir una referencia visual o revisar un borrador mientras conservas los hechos y la voz que deseas mantener.
- DeepSeek-V4.1-FlashConvierte briefings preliminares, problemas de código o notas dispersas en borradores enfocados. Define la tarea, proporciona contexto y solicita la siguiente acción útil.
- Gemini 3.8 FlashConecta el material de origen con un siguiente paso claro. Usa Gemini 3.8 Flash para explicar un documento, comparar detalles en una referencia visual o transformar un brief general en un borrador estructurado que puedes seguir refinando.
- Gemini 4 ArgonDescompón problemas matemáticos, diseña soluciones de código o lee documentos técnicos extensos con Gemini 4 Argon. Combina gráficos y capturas para aclarar los detalles del problema.
- GPT-6.1 SolEntrega requisitos de funcionalidades, cambios de código o capturas de interfaz a GPT-6.1 Sol para definir los próximos pasos accionables. Explica la lógica compleja junto con los requisitos y genera planes de implementación, casos de prueba o documentación técnica.
- GPT-6.1 TerraSube una imagen, un conjunto de notas o un borrador incompleto. Usa GPT-6.1 Terra para explicar los detalles importantes, organizar tu material y darle forma a una redacción clara para tu audiencia objetivo.
- GPT-6 AstraPlantea una pregunta difícil, incluye el material relevante y las restricciones importantes. GPT-6 Astra ayuda a conectar la evidencia, ponderar alternativas y convertir el resultado en un informe claro que puedes seguir refinando.
- Grok 4.7Use Grok 4.7 para revisar código, explicar capturas de pantalla o aclarar una solución técnica compleja. Reúna los requisitos y materiales relacionados para convertir la discusión en listas de pruebas, planes de migración o recomendaciones claras de decisión.
Create and edit images
4- GPT Image 2Crea imágenes de producto, pósters, retratos e ilustraciones a partir de descripciones textuales o imágenes de referencia. Define el sujeto, el estilo y la composición, y luego perfecciona los detalles clave.
- GPT Image 2.5 SunburstCambia la escena mientras conservas el sujeto. Cuando los detalles a preservar son tan importantes como las modificaciones deseadas, GPT Image 2.5 Sunburst te ayuda a crear y refinar tus imágenes.
- GPT Image 2.6 FlareConvierte una idea de publicación o una imagen de referencia en una imagen, un gráfico SVG escalable o un GIF animado con GPT Image 2.6 Flare. Explora diseños y estilos de ilustración, luego describe qué cambiar en la siguiente versión.
- GPT Image 2.6 SunburstCrea imágenes detalladas, arte SVG escalable y GIF animados con GPT Image 2.6 Sunburst. Describe tu sujeto, entorno, luz y composición, o añade imágenes de referencia para desarrollar visuales de campaña y editoriales.
Bring ideas into motion
2- Seedance 2.0Convierte descripciones textuales o imágenes de referencia en secuencias dinámicas. Guía al sujeto, la cámara y la atmósfera para explorar momentos de personajes, mundos ilustrados y narrativas visuales.
- Seedance 2.5Genera escenas de video a partir de briefings escritos o imágenes de referencia. Define el movimiento, la cámara y el estilo visual, luego optimiza cada segmento para contar la historia que deseas.
Compare AI models
AI model research performance
Compare the factual accuracy of AI models when they research information and answer questions. Scores are out of 100; a higher score means more accurate answers on this set of tasks.
| Model | Low | Medium | High |
|---|---|---|---|
| 97.50 | 97.73 | No complete result | |
| 95.76 | 98.59 | 99.55 | |
GPT-6 Luna | 97.90 | 100.00 | 99.32 |
| 83.23 | 95.17 | 97.17 | |
| 91.46 | 96.18 | 97.40 | |
| 80.93 | 87.10 | 80.58 | |
| 89.92 | No complete result | 95.95 | |
| 0.00 | 43.07 | 65.36 |
GPT-6 Astra scored 99.55 for factual accuracy in the completed high-effort research evaluations shown here.
AI model writing performance
Compare how well AI writing models complete content creation tasks and deliver the requested results. Scores are out of 100 and measure task completion rather than article quality.
Original scoring criteria
| Model | Task fulfillment / 100 |
|---|---|
100.00 | |
100.00 | |
GPT-6 Luna | 99.00 |
99.00 | |
99.00 | |
99.00 | |
96.00 | |
95.00 | |
94.00 | |
93.00 |
Updated scoring criteria
AI model feature-use performance
Use tasks such as researching information, writing documents and creating slides to check whether AI models choose the right features and follow instructions. Scores measure feature use, not the quality of the finished articles, images or slides.
- Writing
- Research
- Images
- Slides
- Webpages
| Model | Feature-use score / 100Effort |
|---|---|
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| |
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GPT-6 Luna |
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Results with different scoring rules are shown in separate groups.
How to use
Choose your model
Choose an AI model for research, article writing or summarizing content. Switch between GPT, Claude, Gemini and other models in YouMind to explore different approaches.
Selected: GPT-6.1 Sol
Bring your context
Add PDFs, documents, images or notes, then describe your task. Ask AI to use your reference material to summarize key points, create an article outline or draft content.
Review and refine
Rewrite AI-generated text, refine the wording or select an image area for a local edit. Keep the parts you like and use specific instructions to refine the article or image.
Our Writing Sense analysis
Compare AI writing results and task costs
Compare Writing Sense scores with average agent task costs from the published report.
Writing Sense frente al coste
In the published report's high-effort configurations, Claude Opus 5.5 scored 90.28 for Writing Sense at an average cost of $0.6035 per task. Gemini 3.8 Flash scored 78.85 at $0.1393 per task.
Higher effort did not always produce a higher score on these tasks. GPT-6.1 Sol scored 80.26 for Writing Sense at medium effort and 77.20 at high effort.
View data table
| Model | Effort | Writing Sense score / 100 | Understanding the author's intent / 100 | Following the author's intent in writing / 100 | USD / task |
|---|---|---|---|---|---|
| Claude Opus 5.5 | High | 90.28 | 100.00 | 87.04 | $0.6035 |
| GPT-6 Astra | High | 86.80 | 100.00 | 82.40 | $1.7338 |
| GPT-6.1 Sol | High | 77.20 | 92.59 | 72.07 | $0.4075 |
| Gemini 4 Argon | High | 81.72 | 100.00 | 75.63 | $0.1955 |
| Claude Sonnet 5.5 | High | 64.13 | 66.67 | 63.28 | $0.2787 |
| Claude Opus 4.6 | High | 63.11 | 77.78 | 58.22 | $0.4546 |
| Gemini 3.8 Flash | High | 78.85 | 77.78 | 79.21 | $0.1393 |
| DeepSeek V4.1 Flash | High | 59.96 | 62.96 | 58.96 | $0.0407 |
| GPT-6 Luna | High | 48.06 | 22.22 | 56.68 | $0.0646 |
| Claude Haiku 5.5 | High | 39.31 | 33.33 | 41.31 | $0.0227 |
| GPT-6.1 Terra | High | 73.15 | 77.78 | 71.61 | No comparable cost |
Which AI models understand your source material?
Compare error rates and the choices behind them.
Over-cuttingPolished but wrongOther
| Model | Reading error rate | Among wrong answers |
|---|---|---|
0.0% | No errors in this sample | |
4.9% | Over-cutting: 25.0%Polished but wrong: 75.0%Other: 0.0% | |
6.2% | Over-cutting: 80.0%Polished but wrong: 20.0%Other: 0.0% | |
8.6% | Over-cutting: 14.3%Polished but wrong: 71.4%Other: 14.3% | |
22.2% | Over-cutting: 50.0%Polished but wrong: 0.0%Other: 50.0% | |
23.5% | Over-cutting: 47.4%Polished but wrong: 5.3%Other: 47.4% | |
38.3% | Over-cutting: 67.7%Polished but wrong: 16.1%Other: 12.9% | |
45.7% | Over-cutting: 62.2%Polished but wrong: 13.5%Other: 24.3% | |
71.6% | Over-cutting: 19.0%Polished but wrong: 62.1%Other: 19.0% | |
75.3% | Over-cutting: 26.2%Polished but wrong: 39.3%Other: 32.8% |
View data table
| Model | Error rate | Over-cutting | Polished but wrong | Other |
|---|---|---|---|---|
| Gemini 4 Argon | 0.0% | Not applicable | Not applicable | Not applicable |
| GPT-6 Astra | 4.9% | 25.0% | 75.0% | 0.0% |
| Claude Opus 5.5 | 6.2% | 80.0% | 20.0% | 0.0% |
| GPT-6.1 Sol | 8.6% | 14.3% | 71.4% | 14.3% |
| Claude Opus 4.6 | 22.2% | 50.0% | 0.0% | 50.0% |
| Gemini 3.8 Flash | 23.5% | 47.4% | 5.3% | 47.4% |
| Claude Sonnet 5.5 | 38.3% | 67.7% | 16.1% | 12.9% |
| DeepSeek V4.1 Flash | 45.7% | 62.2% | 13.5% | 24.3% |
| GPT-6 Luna | 71.6% | 19.0% | 62.1% | 19.0% |
| Claude Haiku 5.5 | 75.3% | 26.2% | 39.3% | 32.8% |
How much do AI models write, and do they use the right material?
Can AI models write what you mean after understanding it?
Does reading well mean writing well? Compare model rankings in both tasks.
| Model | Reading | Writing |
|---|---|---|
Rank#1100.0% | Rank#373.2% | |
Rank#295.1% | Rank#275.5% | |
Rank#393.8% | Rank#184.9% | |
Rank#491.4% | Rank#572.0% | |
Rank#577.8% | Rank#757.5% | |
Rank#676.5% | Rank#472.7% | |
Rank#761.7% | Rank#664.1% | |
Rank#854.3% | Rank#855.8% | |
Rank#928.4% | Rank#954.4% | |
Rank#1024.7% | Rank#1048.6% |
When correct reading still leads to a wrong turn
Among the articles a model read correctly every time, how many still drifted from the author’s intent when rewritten?
View data table
| Model | Reading | Writing | Breaks an author choice |
|---|---|---|---|
| Claude Opus 4.6 | 77.8% | 57.5% | 66.7% |
| Claude Haiku 5.5 | 24.7% | 48.6% | No qualifying data |
| Claude Opus 5.5 | 93.8% | 84.9% | 44.4% |
| Claude Sonnet 5.5 | 61.7% | 64.1% | 85.2% |
| DeepSeek V4.1 Flash | 54.3% | 55.8% | 77.8% |
| Gemini 3.8 Flash | 76.5% | 72.7% | 46.3% |
| Gemini 4 Argon | 100.0% | 73.2% | 59.3% |
| GPT-6.1 Sol | 91.4% | 72.0% | 65.1% |
| GPT-6 Astra | 95.1% | 75.5% | 54.0% |
| GPT-6 Luna | 28.4% | 54.4% | No qualifying data |
Make the vase blue.