DeepSeek vs NotebookLM (2026) — Which Is Better?

Comparing DeepSeek and NotebookLM side by side to help you choose the right AI tool for your needs. DeepSeek: DeepSeek's chat app is free; its OpenAI-compatible API is pay-per-token (DeepSeek-V4 from $0.14/M input, $0.28/M output) with thinking mode and a 1M-token context. NotebookLM: Google's AI-powered research and note-taking assistant

DeepSeek

La aplicación de chat de DeepSeek es gratuita; su API compatible con OpenAI es de pago por token (DeepSeek-V4 desde $0,14/M de entrada, $0,28/M de salida) con modo de pensamiento y un contexto de 1 millón de tokens.

DeepSeek offers a free plan with paid tiers for advanced features. Consumer chat app: free on web, iOS, and Android. API (pay-per-token, no subscription; charged against a topped-up balance): deepseek-v4-flash — $0.14 per million input tokens (cache miss) or $0.0028 (cache hit), and $0.28 per million output tokens. deepseek-v4-pro — $0.435 per million input tokens (cache miss) or $0.003625 (cache hit), and $0.87 per million output tokens. Context caching delivers roughly a 50x discount on repeated input tokens. The legacy model names deepseek-chat and deepseek-reasoner now route to deepseek-v4-flash (non-thinking and thinking mode respectively).

DeepSeek Key Features

  • Familia insignia DeepSeek-V4 con modos de pensamiento y no pensamiento unificados
  • Ventana de contexto de 1 millón de tokens con una salida máxima de ~384 000 tokens
  • Aplicación gratuita de chat para consumidores en la web, iOS y Android
  • API de bajo costo compatible con OpenAI con un precio de $0,14 por millón de tokens de entrada
  • Almacenamiento en caché de contexto con grandes descuentos por aciertos de caché (~50 veces más barato la entrada repetida)

Best DeepSeek Use Cases

  • Usar IA poderosa a menor costo
  • Generación y depuración de código.
  • Tareas de razonamiento complejas
  • Investigación sobre LLM de código abierto

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NotebookLM

Google, asistente de investigación y toma de notas de AI

NotebookLM is free to use.

NotebookLM Key Features

  • Subir PDFs, documentos, vídeos, páginas web
  • Respuestas citadas basadas en fuentes
  • Panorama de audio generación de podcast
  • Creación de una guía de estudio
  • Línea de tiempo y generación de preguntas frecuentes

Best NotebookLM Use Cases

  • Análisis de documentos e informes de investigación
  • Estudio a partir de materiales del curso
  • Creación de podcasts a partir de documentos
  • Creación de bases de conocimiento a partir de docs

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Pricing Comparison: DeepSeek vs NotebookLM

DeepSeek: DeepSeek offers a free plan with paid tiers for advanced features. Consumer chat app: free on web, iOS, and Android. API (pay-per-token, no subscription; charged against a topped-up balance): deepseek-v4-flash — $0.14 per million input tokens (cache miss) or $0.0028 (cache hit), and $0.28 per million output tokens. deepseek-v4-pro — $0.435 per million input tokens (cache miss) or $0.003625 (cache hit), and $0.87 per million output tokens. Context caching delivers roughly a 50x discount on repeated input tokens. The legacy model names deepseek-chat and deepseek-reasoner now route to deepseek-v4-flash (non-thinking and thinking mode respectively).

NotebookLM: NotebookLM is free to use.

Preguntas Frecuentes

Which is better: DeepSeek or NotebookLM?

The best choice between DeepSeek and NotebookLM depends on your use case. DeepSeek — DeepSeek's chat app is free; its OpenAI-compatible API is pay-per-token (DeepSeek-V4 from $0.14/M input, $0.28/M output) with thinking mode and a 1M-token context.. NotebookLM — Google's AI-powered research and note-taking assistant. Compare pricing and features above to find the best fit for your workflow.

Is DeepSeek free?

DeepSeek offers a free plan with paid tiers for advanced features. Consumer chat app: free on web, iOS, and Android. API (pay-per-token, no subscription; charged against a topped-up balance): deepseek-v4-flash — $0.14 per million input tokens (cache miss) or $0.0028 (cache hit), and $0.28 per million output tokens. deepseek-v4-pro — $0.435 per million input tokens (cache miss) or $0.003625 (cache hit), and $0.87 per million output tokens. Context caching delivers roughly a 50x discount on repeated input tokens. The legacy model names deepseek-chat and deepseek-reasoner now route to deepseek-v4-flash (non-thinking and thinking mode respectively).

Is NotebookLM free?

NotebookLM is free to use.

What are the best alternatives to DeepSeek and NotebookLM?

Explorar DeepSeek alternatives y NotebookLM alternatives en Nextool.ai para más opciones.

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