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Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite: Benchmarks, Pricing & Speed Comparison

Gemini 2.5 Flash di Google e Gemini 2.5 Flash-Lite di Google sono due modelli di IA di riferimento. Gemini 2.5 Flash offre una finestra di contesto di 1.05M token a $0.30/$2.50 per milione di token, mentre Gemini 2.5 Flash-Lite mette a disposizione 1.05M token di contesto a $0.10/$0.40 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Google

Gemini 2.5 Flash

Inferenza Ultra-Rapida

Gemini 2.5 Flash di Google è un modello di IA progettato per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, con finestra di contesto da 1.0M, velocità di 160 token/s, indice di intelligenza di 68/100 e tarif

Intelligence Index68 / 100
Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Google

Gemini 2.5 Flash-Lite

Modello Leggero ed Economico

Gemini 2.5 Flash-Lite di Google è un modello di IA progettato per la massima efficienza dei costi per token e l’inferenza rapida in produzione, con finestra di contesto da 1.0M, velocità di 220 token/s, indice di intelligenza di 56/100 e ta

Intelligence Index56 / 100
Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Differenze Chiave a Colpo d’Occhio

  • Gemini 2.5 Flash-Lite is 5.1x cheaper for API usage (input + output tokens combined).
  • Gemini 2.5 Flash-Lite is faster at 220 tok/s vs 160 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.5 FlashGemini 2.5 Flash-Lite
Intelligence Index
Composite reasoning & knowledge score (0-100)
6856
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$0.30 / 1M$0.10 / 1M
Output Price
Cost per million output tokens
$2.50 / 1M$0.40 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.36 / 1M$0.08 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text1.05M tokens~1,573 A4 pages of text
Max Output Tokens
Per single request
66K33K
Throughput Speed
Tokens generated per second
160 tok/s220 tok/s
SWE-bench Verified
Real-world software engineering
58.2%N/A
GPQA Diamond
Graduate-level reasoning
75.4%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.07 / 1M$0.03 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 2.5 Flash-Lite
5.1x cheaper monthly runtime
Speed
Gemini 2.5 Flash-Lite
+38% faster generation
Context
Tied
1.05M tokens window

Punteggi Benchmark Verificati

Official evaluation metrics verified by independent third-party research labs.

Gemini 2.5 FlashGemini 2.5 Flash-Lite
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

58.2%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

75.4%vsN/A
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

83.2%vs76.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1385ptsvs1330pts
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

84.5%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs220 tok/s

Latenza e Tempo di Risposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Gemini 2.5 Flash0.45s
Gemini 2.5 Flash-Lite0.32s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.5 Flash3.58s
Gemini 2.5 Flash-Lite2.59s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Gemini 2.5 Flash Monthly API Bill
$2.81 / month
$0.3/1M in · $2.5/1M out
Gemini 2.5 Flash-Lite Monthly API Bill
$0.55 / month
$0.1/1M in · $0.4/1M out
Gemini 2.5 Flash-Lite saves approximately $2.26 / month (81%) under this workload.5.1x Savings

Gemini 2.5 Flash · Strengths & Key Advantages

  • Finestra di contesto da 1.0M con capacità massima di output fino a 66K token (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
  • Throughput elevato di 160 token/secondo con latenza al primo token (TTFT) di soli 450 ms
  • Economia API competitiva ($0.3/$2.5 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

  • Finestra di contesto da 1.0M con capacità massima di output fino a 33K token (MMLU-Pro 76.5% · Arena Elo 1330)
  • Throughput elevato di 220 token/secondo con latenza al primo token (TTFT) di soli 320 ms
  • Economia API competitiva ($0.1/$0.4 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGemini 2.5 FlashGemini 2.5 Flash-Lite
Cost per Task
Estimated USD to finish one task
$0.85$0.35
Output Tokens / Task
Tokens generated per task
32K12K
Reasoning Tokens / Task
Thinking tokens burned per task
14K4K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.5 FlashGemini 2.5 Flash-Lite
Official API Model ID (SDK)models/gemini-2-5-flashmodels/gemini-2-5-flash-lite
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-062025-06
Knowledge CutoffMarch 2025March 2025
ArchitectureHigh-throughput sparse multimodal transformer with thinking modeCompact multimodal transformer with lightweight thinking
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.075/1M with configurable TTLImplicit + Explicit Context Caching at $0.025/1M with configurable TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationVertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationGoogle DeepMind Frontier Safety Framework VerifiedGoogle DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, vision, audio, videotext, vision
Output Modalitiestexttext

Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite: Risposte Rapide (FAQ)

Which is more intelligent, Gemini 2.5 Flash or Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash is more intelligent. It scores 68 compared with 56 on the composite Intelligence Index.

Which model is faster?

Gemini 2.5 Flash-Lite is faster, generating 220 tokens per second compared with 160 tokens per second.

Which model is cheaper to run?

Gemini 2.5 Flash-Lite is cheaper at $0.08 per 1M tokens blended, compared with $0.36 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 2.5 Flash-Lite has lower latency, with a time to first token of 0.32s compared with 0.45s.

Verdetto

Sia Gemini 2.5 Flash (Ideale per le interazioni in tempo reale a bassissima latenza e il routing ad alto volume, sistemi RAG aziendali e integrazioni API scalabili.) sia Gemini 2.5 Flash-Lite (Ideale per la massima efficienza dei costi per token e l’inferenza rapida in produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Gemini 2.5 Flash guida nei benchmark di ragionamento e programmazione, Gemini 2.5 Flash-Lite garantisce una generazione più rapida e Gemini 2.5 Flash-Lite offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Gemini 2.5 Flash o Gemini 2.5 Flash-Lite?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Gemini 2.5 Flash. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Gemini 2.5 Flash e Gemini 2.5 Flash-Lite?+

Gemini 2.5 Flash costa $0.30 / $2.50 per milione di token di input/output, mentre Gemini 2.5 Flash-Lite costa $0.10 / $0.40. Nel costo combinato, Gemini 2.5 Flash-Lite risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Gemini 2.5 Flash supporta 1.05M token di contesto contro 1.05M token di Gemini 2.5 Flash-Lite, mentre Gemini 2.5 Flash-Lite offre una velocità di generazione superiore.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fonti ufficiali: Documentazione API ufficiale di Google e Google, schede di sistema e benchmark indipendenti (2026).