Head-to-Head Model Comparison

Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien

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Gemini 2.5 FlashProfile

Gemini 2.5 Flash-LiteProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 2.5 Flash

Ultraschnelle Echtzeit-Inferenz

Gemini 2.5 Flash von Google ist ein KI-Modell für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing mit 1.0M Kontextfenster, 160 Token/s Durchsatz, einem Intelligenz-Index von 68/100 und $0.3/$2.5 pro 1M Token.

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

Kompaktes Effizienz-Modell

Gemini 2.5 Flash-Lite von Google ist ein KI-Modell für maximale Kosteneffizienz pro Token und ressourcenschonende Produktions-Workloads mit 1.0M Kontextfenster, 220 Token/s Durchsatz, einem Intelligenz-Index von 56/100 und $0.1/$0.4 pro 1M

Intelligence Index56 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

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 →

Feature	Gemini 2.5 Flash	Gemini 2.5 Flash-Lite
Intelligence Index Composite reasoning & knowledge score (0-100)	68	56
Provider	Google	Google
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 text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	66K	33K
Throughput Speed Tokens generated per second	160 tok/s	220 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

Wer gewinnt in welcher Disziplin?

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

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Latenz & Antwortzeit

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

Interaktiver Token-Kosten-Simulator

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

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% 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

1.0M Kontextfenster und bis zu 66K maximale Output-Token (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
Hohe Generierungsgeschwindigkeit von 160 Token/Sekunde bei nur 450 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($0.3/$2.5 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe

Considerations & Trade-offs

Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

1.0M Kontextfenster und bis zu 33K maximale Output-Token (MMLU-Pro 76.5% · Arena Elo 1330)
Hohe Generierungsgeschwindigkeit von 220 Token/Sekunde bei nur 320 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($0.1/$0.4 pro 1M Token) inklusive Prompt-Caching, Tool-Calling und strikter JSON-Ausgabe

Considerations & Trade-offs

Proprietäres Cloud-Modell ohne Möglichkeit zum lokalen Download der Modellgewichte
Bei extrem komplexen mehrstufigen Forschungsfragen bieten schwere Reasoning-Spezialmodelle noch tiefere Analysen

Token Use & Task Economics

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

Metric	Gemini 2.5 Flash	Gemini 2.5 Flash-Lite
Cost per Task Estimated USD to finish one task	$0.85	$0.35
Output Tokens / Task Tokens generated per task	32K	12K
Reasoning Tokens / Task Thinking tokens burned per task	14K	4K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite: Schnelle Antworten (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.

Fazit

Sowohl Gemini 2.5 Flash (Optimal für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Gemini 2.5 Flash-Lite (Optimal für maximale Kosteneffizienz pro Token und ressourcenschonende Produktions-Workloads, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Gemini 2.5 Flash führt bei komplexem Reasoning und Coding, Gemini 2.5 Flash-Lite liefert den höheren Token-Durchsatz und Gemini 2.5 Flash-Lite ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Gemini 2.5 Flash oder Gemini 2.5 Flash-Lite?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Gemini 2.5 Flash vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Gemini 2.5 Flash und Gemini 2.5 Flash-Lite?+

Gemini 2.5 Flash kostet $0.30 / $2.50 pro 1M Input-/Output-Tokens, Gemini 2.5 Flash-Lite liegt bei $0.10 / $0.40. Beim gewichteten Gesamtpreis ist Gemini 2.5 Flash-Lite günstiger.

Welches Modell hat das größere Kontextfenster und die höhere Geschwindigkeit?+

Gemini 2.5 Flash bietet 1.05M Tokens Kontext gegenüber 1.05M Tokens bei Gemini 2.5 Flash-Lite. Bei der Generierungsgeschwindigkeit liegt Gemini 2.5 Flash-Lite vorn.

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 & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Feature	Gemini 2.5 Flash	Gemini 2.5 Flash-Lite
Official API Model ID (SDK)	models/gemini-2-5-flash	models/gemini-2-5-flash-lite
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-06	2025-06
Knowledge Cutoff	March 2025	March 2025
Architecture	High-throughput sparse multimodal transformer with thinking mode	Compact multimodal transformer with lightweight thinking
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	10,000 – 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 tokens	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Implicit + Explicit Context Caching at $0.075/1M with configurable TTL	Implicit + Explicit Context Caching at $0.025/1M with configurable TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	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	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Vertex AI Supervised Adapter Tuning & Context Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text 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 VRAM	Cloud-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 Classification	Google DeepMind Frontier Safety Framework Verified	Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision, audio, video	text, vision
Output Modalities	text	text

Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite

Beliebige Modelle wechseln & vergleichen

Gemini 2.5 Flash

Gemini 2.5 Flash-Lite

Wer gewinnt in welcher Disziplin?

Geprüfte Benchmark-Ergebnisse im Vergleich

Latenz & Antwortzeit

Interaktiver Token-Kosten-Simulator

Gemini 2.5 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Technische Spezifikationen

Gemini 2.5 Flash vs Gemini 2.5 Flash-Lite: Schnelle Antworten (FAQ)

Fazit

Häufig gestellte Fragen (FAQ)

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