DeepSeek V4.1 Flash (Reasoning, Max Effort)
Descripción
DeepSeek-V4.1-Flash is an MIT-licensed multimodal Mixture-of-Experts model accepting images and text and generating text. It has 552B backbone parameters, 196B Engram conditional-memory parameters, and approximately 763B parameters in the released checkpoint. Its causal encoder-decoder architecture activates 8B parameters per token during prefill and 16B during decode. Trained on 45T multimodal tokens, it supports a 1M-token context, up to 384K output tokens on the DeepSeek API, and continuously adjustable reasoning effort from 1 to 100. CSA2 attention and FP4 KV caching reduce global KV cache storage to 890 bytes per token. The API model name is deepseek-flash. Catalog prices are peak rates per million tokens: $0.30 input, $0.006 cached input, and $1.20 output. Off-peak rates are $0.15, $0.003, and $0.60 respectively, effective September 10, 2026 at 04:00 UTC. Peak hours are 01:00–04:00 and 06:00–10:00 UTC on weekdays; all other times are off-peak (the launch pricing announcement also lists public holidays as off-peak).
Radar de capacidades
Rankings
| Dominio | #Posición | Puntuación | Fuente |
|---|---|---|---|
| Capacidad agéntica | 41 | 49.0 | LS |
| Ranking de codificación | 7 | 95.0 | AA |
| Ranking general | 56 | 72.0 | AA |
| Razonamiento matemático | 13 | 93.0 | LB |
| Ranking multimodal | 4 | 73.0 | LS |
| Razonamiento | 20 | 87.0 | LB |
| Ciencia | 95 | 72.0 | AA |
Puntuaciones de benchmarks (LLM Stats)
(LLM Stats (zeroeval))Agents
Code
Math
Reasoning
Vision
Índices de evaluación AA
(Artificial Analysis)Puntuaciones por categoría LLM Stats
(LLM Stats (zeroeval))Precios
Velocidad
Ranking de Precios por Proveedor
Ranking de Precios por Proveedor
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