Gemini 3.5 Flash — Specifiche
Compiled by Mustafa Ihsan from the vendor’s published documentation · Last updated
| Sviluppatore | |
|---|---|
| Tipo | LLM (multimodale) |
| Modalità | Testo, immagine, audio, video → Testo |
| Parametri | Non divulgato |
| Finestra contestuale | 1 milione |
| Output massimo | 65K |
| Licenza | Proprietaria |
| Pesi aperti | No |
| Pubblicato | 2026 |
| Prezzo dell’input | $1.50 /1M |
| Prezzo dell’output | $9.00 /1M |
| Provider 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
| Input (per ogni milione di token) | $1.50 |
|---|---|
| Output (per ogni milione di token) | $9.00 |
| Rapporto output/input | 6× |
| Combinato (4:1 in:out) | $3.00 per 1 milione di token |
What Gemini 3.5 Flash costs per month
Spesa mensile reale con un mix input-to-output 4:1 — il rapporto effettivamente prodotto da un tipico carico di lavoro basato su chat o RAG.
| Carico di lavoro | Token/mese | Costo/mese |
|---|---|---|
| Progetto secondario | 1 milione in ingresso / 0,25 milioni in uscita | $3.75 |
| Piccolo team | 20 milioni in ingresso / 5 milioni in uscita | $75 |
| Produzione | 200 milioni in ingresso / 50 milioni in uscita | $750 |
Calcola i tuoi numeri personalizzati nel Calcolatore dei costi delle API per l'IA.
Cheaper alternatives to Gemini 3.5 Flash
| Modello | Costo combinato ($/1 milione) | Risparmi |
|---|---|---|
| GLM 5.2 aperta | $2.00 | il 33% più economico |
| DeepSeek V4-Pro aperta | $0.522 | 83% cheaper |
| Kimi K2.7 Code aperta | $0.980 | 67% più economico |
Domande frequenti
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.
Confronta i prezzi di tutti i modelli Gemini uno accanto all’altro: Prezzi dell'API Gemini.
I prezzi indicati sono le tariffe ufficiali pubblicate per l'API principale del modello e vengono aggiornati man mano che i fornitori li modificano. Sconti per volumi elevati, elaborazione batch e input memorizzati nella cache non sono inclusi. Confronta tutti i modelli fianco a fianco nel Database di modelli IA o il Classifica LLM.