Gemini 3.5 Flash — Especificaciones
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Desarrollador | |
|---|---|
| Tipo | LLM (multimodal) |
| Modalidad | Texto, imagen, audio y vídeo → Texto |
| Parámetros | No revelado |
| Ventana de contexto | 1 millón |
| Salida máxima | 65 000 |
| Licencia | Propietario |
| Pesos abiertos | No |
| Lanzado | 2026 |
| Precio de entrada | $1.50 /1M |
| Precio de salida | $9.00 /1M |
| Proveedores de API | Google AI Studio, Vertex AI |
What is Gemini 3.5 Flash?
Gemini 3.5 Flash is Google’s fast multimodal model, and an unusual case of a cheaper tier
beating the more expensive one on the benchmarks most people care about: it outperforms
Gemini 3.1 Pro on coding and agentic tasks while running roughly 4× faster and about 25%
cheaper, with the same 1M-token context. Pricing is $1.50 in / $9 out per million tokens.
When the faster, cheaper model also scores higher, the “Pro” tier stops being the default
and becomes a specialist choice. For coding assistants, agent loops and anything where a user
is waiting on a response, 3.5 Flash is the better pick on every axis at once — a rare thing
in model selection, where speed, cost and quality usually trade against each other. Reserve
3.1 Pro for workloads that specifically need its multimodal depth. The one caveat is the same
one that applies across the Gemini line: check the long-context billing terms for your tier
before building a feature that routinely sends very large prompts, because the headline rate
is not always the rate you pay above 200K tokens.
Gemini 3.5 Flash pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $1.50 |
|---|---|
| Salida (por cada millón de tokens) | $9.00 |
| Relación salida/entrada | 6× |
| Combinada (4:1 entrada:salida) | $3.00 por 1 millón de tokens |
What Gemini 3.5 Flash costs per month
Gasto mensual real con una mezcla entrada:salida de 4:1, es decir, la proporción que realmente genera una carga de trabajo típica de chat o RAG.
| Carga de trabajo | Tokens/mes | Coste mensual |
|---|---|---|
| Proyecto secundario | 1 millón de tokens de entrada / 0,25 millones de tokens de salida | $3.75 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $75 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $750 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to Gemini 3.5 Flash
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| GLM 5.2 abierta | $2.00 | un 33 % más barata |
| DeepSeek V4-Pro abierta | $0.522 | 83% cheaper |
| Kimi K2.7 Code abierta | $0.980 | un 67 % más barato |
Preguntas frecuentes
How much does Gemini 3.5 Flash cost per 1M tokens?
Gemini 3.5 Flash costs $1.50 per 1M input tokens and $9.00 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $3.00 per 1M tokens.
How much does Gemini 3.5 Flash cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $75 on Gemini 3.5 Flash. A side project (1M in / 0.25M out) costs roughly $3.75.
What is a cheaper alternative to Gemini 3.5 Flash?
GLM 5.2 is the strongest cheaper option in our database at $2.00 per 1M blended — about 33% less than Gemini 3.5 Flash. It is also open-weight, so self-hosting is an option.
Can I run Gemini 3.5 Flash locally?
No. Gemini 3.5 Flash is a closed, API-only model — the weights are not released, so it cannot be self-hosted.
Why does Gemini 3.5 Flash charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. Gemini 3.5 Flash charges 6× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Compare los precios de todos los modelos Gemini uno al lado del otro: Precios de la API Gemini.
Los precios corresponden a las tarifas oficiales publicadas para la API principal del modelo y se revisan periódicamente conforme los proveedores los actualicen. No incluyen descuentos por volumen, procesamiento por lotes ni entradas en caché. Compare todos los modelos uno al lado del otro en la Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).