Ling 3.0 Flash Fin
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment workflows that require complex multi-step tasks and long-horizon planning and execution, while retaining general capabilities in reasoning, coding, and mathematics.
inclusionai/ling-3.0-flash-fin
- Contexto
- 262k tokens
- Máx. completion
- 235,929
- Tools
- Sí
- JSON
- Sí
- Lanzamiento
- 2026-08-27
Llámalo desde Geek Hub
El mismo SDK de OpenAI. Cambia el base URL y el id del modelo.
curl https://api.geekhub.mx/v1/chat/completions \
-H "Authorization: Bearer $GEEKHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "inclusionai/ling-3.0-flash-fin",
"messages": [{"role": "user", "content": "Hola"}]
}'Consigue tu API keyPreguntas frecuentes
- ¿Qué es Ling 3.0 Flash Fin?
- Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment workflows that require complex multi-step tasks and long-horizon planning and execution, while retaining general capabilities in reasoning, coding, and mathematics. Ling 3.0 Flash Fin corre en el API de Geek Hub (compatible con OpenAI). Id: inclusionai/ling-3.0-flash-fin.
- ¿Ling 3.0 Flash Fin es gratis?
- No. El input cuesta $0.0654 / 1M tokens y el output $0.1962 / 1M tokens en Geek Hub (markup incluido).
- ¿Cuál es el contexto de Ling 3.0 Flash Fin?
- Ling 3.0 Flash Fin tiene una ventana de 262k tokens. Soporta hasta 235,929 tokens de completion.
- ¿Ling 3.0 Flash Fin soporta tool calling y structured outputs?
- Ling 3.0 Flash Fin acepta tools y tool_choice para function calling. También soporta structured outputs con un JSON schema en response_format.
- ¿Cuándo se lanzó Ling 3.0 Flash Fin?
- Ling 3.0 Flash Fin se lanzó el 27 de agosto de 2026.
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Ling-3.0-flash*Ling-3.0-flash* is a *124B-parameter Mixture-of-Experts (MoE) model*, with approximately *5.1B parameters activated per token*. The model is designed with *token efficiency and pr