Official API Model ID (SDK String): models/gemini-3-5-flash-lite
Supported SDK & API Protocol: Google Gemini API (generateContent) + OpenAI-Compatible SDK
Lifecycle & Deprecation Status: Active GA (Guaranteed support through 2028+)
Production Rate Limits (RPM & TPM): 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Pricing Tier (>128K / >200K): Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Write & TTL Policy: Implicit + Explicit Context Caching at $0.1/1M with configurable TTL
Computer Use & Browser GUI Agent: Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling: Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Code Sandbox: Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Fine-Tuning & Distillation Support: Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Tokenization Billing: Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Weights Precision & Quantization: Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
Minimum GPU VRAM Requirement: Zero Local VRAM Required (100% Serverless Cloud API)
Supported Inference Engines: Managed Google Cloud API
System Card & Safety Framework: Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (SOC2 / HIPAA / ZDR): SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier

Engineering & Pricing Workbench

Gemini 3.5 Flash-Lite Cost, Context, Hardware & API Integration

Daily API Requests:500 / day

Avg Input Tokens per Request:4,000 tok

Avg Output Tokens per Request:1,000 tok

Conversation Depth (History Re-billing):1 Turn (Single-Shot)

Prompt Cache Hit Rate:($0.1/1M cached)50%

Estimated Monthly API Cost (30 Days)

$45.00$54.00

Monthly Savings: $9.00 (Caching/Batch)

Daily Cost:: $1.50
Cost per Request:: $0.00300
Effective Input / 1M:: $0.250
Effective Output / 1M:: $2.000

Subscription ($20/mo) vs API

For single-user chat, a $20/mo subscription caps your bill below this API volume.

Break-even point: ~222 requests/day equals $20/month.

Same Monthly Workload Cost Across Popular Reference Models

Gemini 3.5 Flash-Lite (Active)

$45.00

/ month

Gemini 2.5 Flash

$18.00

/ month

DeepSeek V3

$32.70

/ month

GPT-4o

$300.00

/ month

Claude 3.7 Sonnet

$405.00

/ month

Live Prompt Paste Tokenizer & Cost Counter

Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.

Chars / Words

175 / 24

OpenAI o200k

~46 tok

Claude BPE

~49 tok

Llama / DeepSeek

~51 tok

Hybrid Prompt Routing Cascade Simulator

Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Gemini 3.5 Flash-Lite:

Cascaded Monthly Bill:$24.75/mo

Saves $20.25/mo (45% cost reduction) vs sending 100% of traffic to Gemini 3.5 Flash-Lite.

Benchmark Scores & 6-Axis Capability Radar

Benchmark Encyclopedia

Gemini 3.5 Flash-Lite2026 Frontier Median

MMLU-Pro: 81.2%
HumanEval: 89.5%
Chatbot Arena Elo: 1375pts

Strengths

Economical élevé-volume tarification
rapide exécution avec faible latence
1M fenêtre de contexte

Limitations & Trade-offs

moins adept à profond mathématique proofs
texte et vision seulement (no audio entrée)

Editorial Assessment

coût-effective, fiable bourreau de travail pour scalable subagent architectures.

Best for: autonome subagent boucles, résumé, et données transformation

Compare Gemini 3.5 Flash-Lite

Gemini 3.5 Flash-Lite vs Grok 4.6 Gemini 3.5 Flash-Lite vs Gemini 3.6 Flash Gemini 3.5 Flash-Lite vs GPT-5.6 Luna Gemini 3.5 Flash-Lite vs GPT-6 Astra Gemini 3.5 Flash-Lite vs Claude Opus 5.5 Gemini 3.5 Flash-Lite vs GPT-6.1 Sol Gemini 3.5 Flash-Lite vs Llama 5

Frequently Asked Questions about Gemini 3.5 Flash-Lite

How much does the Gemini 3.5 Flash-Lite API cost per 1M tokens?+

Gemini 3.5 Flash-Lite by Google is priced at $0.4 per 1M input tokens and $2 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.1 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.

Should I use a $20/month subscription or the Gemini 3.5 Flash-Lite pay-as-you-go API?+

A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.

How many words and pages fit in Gemini 3.5 Flash-Lite's context window?+

Gemini 3.5 Flash-Lite features a 1.0M tokens context window, which equals approximately 786,432 English words or ~2,097 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 32,768 tokens.

Can I run Gemini 3.5 Flash-Lite locally on my own GPU (Open Weights)?+

No, Gemini 3.5 Flash-Lite is a proprietary closed-weights model hosted by Google. It cannot be downloaded for local GPU execution and must be accessed via Google's official API or cloud platform.

Does Google train on data sent to the Gemini 3.5 Flash-Lite API, and is commercial use allowed?+

API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Google Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Google AI Studio API, Google Cloud Vertex AI.

How does Gemini 3.5 Flash-Lite perform on coding and reasoning benchmarks?+

Gemini 3.5 Flash-Lite achieves a composite Intelligence Index of 69/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 81.2% on MMLU-Pro, and 1375 pts on Chatbot Arena Elo.

What is Gemini 3.5 Flash-Lite best used for?+

Gemini 3.5 Flash-Lite is best suited for: autonome subagent boucles, résumé, et données transformation. Assessment: coût-effective, fiable bourreau de travail pour scalable subagent architectures.

Google Family Lineage, Routing Tiers & Upgrade Path

Step down to a lighter sibling for high-volume routing or step up to Google's flagship reasoning tier:

Higher-Intelligence Upgrade2026-09

AI Glossary & Architecture Concepts

View full glossary →

Key machine learning concepts and benchmarks relevant to Gemini 3.5 Flash-Lite:

Jeton (Token)

L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.

Benchmark (Banc d’essai)

Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).

Fenêtre de contexte

Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.

Modèle de raisonnement

Un modèle d'IA entraîné par apprentissage par renforcement pour allouer du temps de calcul à la réflexion logique avant d'émettre une solution, idéal pour les problèmes scientifiques et le code complexe.

Chaîne de pensée (CoT)

Une méthode de raisonnement pas-à-pas où le modèle décompose le problème en étapes logiques intermédiaires avant de conclure, augmentant drastiquement la précision en mathématiques et programmation.

Appel d'outils (Tool Calling)

La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.

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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: Google Cloud Vertex AI Pricing↗

Gemini 3.5 Flash-Lite

Technical Specifications

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