Modelos

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 3.6 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.

Inkling

Thinking Machines Lab's open-weights general-purpose multimodal Mixture-of-Experts model with 975B total parameters and 41B active parameters. Inkling accepts text, image, and audio inputs, produces text, and is designed for agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation.

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.

Nemotron 3 Ultra

NVIDIA's flagship open 550B-parameter Mixture-of-Experts model with 55B active parameters, built for frontier reasoning and orchestration in long-running agentic systems. Features hybrid Mamba-Transformer architecture, LatentMoE routing, multi-token prediction, and NVFP4 precision for 5x higher throughput. Achieves 30% lower cost-to-task-completion on agentic benchmarks. Supports 1M+ token context window with 95% accuracy on Ruler@1M.

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 3.1 Flash-Lite

Google's most cost-efficient Gemini model optimized for high-volume, low-latency use cases. Delivers 2.5x faster time to first token versus Gemini 2.5 Flash with full multimodal support. Ideal for agentic tasks, data extraction, translation, and classification.

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-5.4 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.

Nemotron 3 Super 120B

NVIDIA's open hybrid Mamba-Transformer MoE model with 120B total parameters (12B active). Features 1M token context window and excels at agentic reasoning, coding, planning, and tool calling.

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.

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.

Gemini 2.5 Flash

Google's cost-effective model optimized for high throughput tasks. Balances speed and intelligence with strong multimodal capabilities and 1M token context window.

Llama 4 Scout

Meta's efficient MoE model with 17B active parameters (109B total, 16 experts). Supports up to 10M token context — the longest of any production model. Strong performance on reasoning and multilingual tasks.

Llama 4 Maverick

Meta's quality-focused MoE model with 17B active parameters (400B total, 128 experts). Targets quality-critical tasks with benchmark scores competitive with GPT-4o and Gemini 2.5 Pro.