Modelos
Explora 21 modelos LLM canónicos de todos los proveedores
Algunas descripciones forman parte del piloto de traducción automática y aún no han sido revisadas.
Gemini 3.6 Flash
Google DeepMind's workhorse Flash model that builds on Gemini 3.5 Flash with better coding, knowledge work, and multimodal performance while reducing output token usage by roughly 17% per the Artificial Analysis Index. Natively multimodal across text, image, audio, and video with a 1M-token context window, configurable thinking levels, and built-in computer use, tuned for scaling agentic workflows at a lower cost per output token.
Gemini 3.5 Flash-Lite
Google's fastest and most cost-effective Gemini 3.5-class model, delivering around 350 output tokens per second per the Artificial Analysis Index. Designed for low-latency and high-throughput agentic workflows such as agentic search and document processing, with configurable thinking levels, built-in computer use, and full multimodal support across a 1M-token context window.
Gemini 3.5 Flash Cyber
A specialized, cyber-focused Gemini model built on top of Gemini 3.5 Flash and fine-tuned for finding and fixing cybersecurity vulnerabilities at a lower price per token than larger models. Deployed within Google's CodeMender code security agent, where multiple 3.5 Flash Cyber agents collaborate to reach competitive frontier performance on benchmarks like CyberGym. Given its dual-use nature, it is available exclusively to governments and trusted partners via CodeMender as a limited-access pilot.
Gemini 3.5 Pro
El modelo insignia Gemini de Google DeepMind, reconstruido sobre una base nueva con una ventana de contexto de 2 millones de tokens y un modo de razonamiento Deep Think para las tareas más difíciles de matemáticas, programación y multimodalidad. Es multimodal de forma nativa para texto, imagen, audio y vídeo, con llamadas de función en streaming y una sólida fundamentación en contextos largos.
GPT-5.6 Terra
La opción equilibrada de la serie GPT-5.6 de OpenAI, que intercambia una pequeña parte de la calidad máxima por una latencia y un coste notablemente menores. Conserva sólidas capacidades de razonamiento, programación y uso de herramientas por agentes, con esfuerzo de razonamiento configurable, por lo que resulta adecuada como opción predeterminada para cargas de producción que necesitan capacidades de vanguardia a escala.
GPT-5.6 Sol
El modelo insignia de la serie GPT-5.6 de OpenAI, que mejora la programación, el razonamiento científico, la planificación a largo plazo y los flujos de trabajo con agentes, al tiempo que aumenta la fiabilidad y la eficiencia en tareas reales exigentes. Añade un nivel máximo de esfuerzo de razonamiento y un modo ultra que inicia subagentes para trabajos complejos de varios pasos.
Claude Sonnet 5
El modelo de clase Sonnet más capaz de Anthropic, que lleva capacidades de vanguardia en programación, agentes y trabajo profesional al nivel intermedio, reduciendo la diferencia con Opus 4.8 a un precio menor. Admite pensamiento adaptativo con niveles de esfuerzo de razonamiento seleccionables, una ventana de contexto de un millón de tokens y entradas de texto, imagen y archivos. Su nombre en clave es Fennec.
MiniMax M3
MiniMax's frontier open-weight model with 1M-token context window, native multimodality (text, image, video), and strong coding capabilities. Built on MiniMax Sparse Attention (MSA) architecture, achieving 59% on SWE-Bench Pro with significantly improved efficiency at long context.
Palmyra X5
Writer's most advanced adaptive reasoning model with a 1 million token context window. Processes full million-token prompts in approximately 22 seconds with multi-turn function calls in 300ms. Optimized for enterprise agentic AI workflows at 3-4x lower cost than GPT-4.1.
Gemini 3.5 Flash
Google DeepMind's balanced Gemini 3.5 model that pairs Pro-line reasoning quality with Flash-line latency and cost. Natively multimodal across text, image, audio, and video with a 1M-token context window, configurable thinking levels, and streaming function calling, tuned for high-throughput production workloads.
Gemini 3 Flash
Google's balanced model combining Gemini 3 Pro's reasoning capabilities with the Flash line's latency, efficiency, and cost. Features configurable thinking levels, multimodal function responses, and streaming function calling for complex agentic workflows.
GPT-5.5
OpenAI's most capable model designed for complex real-world work including coding, online research, information analysis, and document creation. Features advanced agentic capabilities with tool search and multi-step task execution.
GPT-5.4 Mini
OpenAI's compact reasoning model optimized for coding, computer use, and subagent tasks. Approaches GPT-5.4 performance on several benchmarks while running more than 2x faster.
Grok 4.3
xAI's latest and most intelligent model with strong agentic tool calling, minimal hallucinations, and configurable reasoning. Supports 1M token context window with competitive pricing.
GPT-5.4
OpenAI's frontier reasoning model combining advances in coding, reasoning, and agentic workflows. Features 1.1M token context window and strong performance on complex multi-step problems.
Gemini 3.1 Pro
El último modelo multimodal insignia de Google, con rendimiento de vanguardia en razonamiento, programación y comprensión multimodal. Incluye uso nativo de herramientas, fundamentación y una ventana de contexto de un millón de tokens.
Kimi K2.6
Moonshot AI's latest model with ultra-long context window support, strong reasoning capabilities, and excellent performance on complex multi-step tasks. Known for reliable long-document understanding.
Grok 4.20
xAI's multi-agent capable model with 2M token context window. Available in reasoning, non-reasoning, and multi-agent variants for diverse enterprise workloads.
Grok 4.1 Fast
xAI's fast and cost-effective model with 2M token context window. Offers both reasoning and non-reasoning modes at significantly lower pricing than flagship models.
Gemini 2.5 Pro
Google's high-capability reasoning model with adaptive thinking for complex agentic and multimodal challenges. Features 1M token context window and strong performance on coding and scientific tasks.