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Gemini 3.6 Flash vs Gemini 3.5 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 3.6 Flash vs Gemini 3.5 Flash-Lite: Benchmarks, Pricing & Speed Comparison

Gemini 3.6 Flash von Google und Gemini 3.5 Flash-Lite von Google gehören zu den führenden KI-Modellen. Gemini 3.6 Flash bietet ein Kontextfenster von 1.05M Tokens bei API-Preisen von $0.75/$3.75 pro 1M Tokens, während Gemini 3.5 Flash-Lite 1.05M Tokens Kontext zu $0.40/$2.00 pro 1M Tokens bereitstellt. Hier finden Sie den vollständigen Benchmark-, Latenz- und Kostenvergleich.

Direktvergleich (VS)

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Google

Gemini 3.6 Flash

Spitzenmodell für Programmierung

Gemini 3.6 Flash von Google ist ein KI-Modell für autonomes Software-Engineering, Code-Refactoring und komplexe Fehleranalyse mit 1.0M Kontextfenster, 185 Token/s Durchsatz, einem Intelligenz-Index von 84/100 und $0.75/$3.75 pro 1M Token.

Intelligence Index84 / 100
Input Token:

$0.75 / 1M

Output Token:

$3.75 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

72%

Google

Gemini 3.5 Flash-Lite

Ultraschnelle Echtzeit-Inferenz

Gemini 3.5 Flash-Lite von Google ist ein KI-Modell für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing mit 1.0M Kontextfenster, 240 Token/s Durchsatz, einem Intelligenz-Index von 69/100 und $0.4/$2 pro 1M Token.

Intelligence Index69 / 100
Input Token:

$0.40 / 1M

Output Token:

$2.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

  • Gemini 3.5 Flash-Lite is 1.9x cheaper for API usage (input + output tokens combined).
  • Gemini 3.5 Flash-Lite is faster at 240 tok/s vs 185 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 3.6 FlashGemini 3.5 Flash-Lite
Intelligence Index
Composite reasoning & knowledge score (0-100)
8469
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$0.75 / 1M$0.40 / 1M
Output Price
Cost per million output tokens
$3.75 / 1M$2.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.66 / 1M$0.35 / 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
185 tok/s240 tok/s
SWE-bench Verified
Real-world software engineering
72%N/A
GPQA Diamond
Graduate-level reasoning
82.4%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.19 / 1M$0.10 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 3.5 Flash-Lite
1.9x cheaper monthly runtime
Speed
Gemini 3.5 Flash-Lite
+30% faster generation
Context
Tied
1.05M tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Gemini 3.6 FlashGemini 3.5 Flash-Lite
SWE-bench Verified (Autonomous Coding)

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

72%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

82.4%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

87.8%vs81.2%
LMSYS Chatbot Arena Elo

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

1460ptsvs1375pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

185 tok/s vs240 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 3.6 Flash0.37s
Gemini 3.5 Flash-Lite0.29s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 3.6 Flash3.07s
Gemini 3.5 Flash-Lite2.37s

Interaktiver Token-Kosten-Simulator

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 3.6 Flash Monthly API Bill
$4.78 / month
$0.75/1M in · $3.75/1M out
Gemini 3.5 Flash-Lite Monthly API Bill
$2.55 / month
$0.4/1M in · $2/1M out
Gemini 3.5 Flash-Lite saves approximately $2.23 / month (47%) under this workload.1.9x Savings

Gemini 3.6 Flash · Strengths & Key Advantages

  • 1.0M Kontextfenster und bis zu 66K maximale Output-Token (SWE-bench Verified 72% · GPQA Diamond 82.4%)
  • Hohe Generierungsgeschwindigkeit von 185 Token/Sekunde bei nur 370 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.75/$3.75 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 3.5 Flash-Lite · Strengths & Key Advantages

  • 1.0M Kontextfenster und bis zu 33K maximale Output-Token (MMLU-Pro 81.2% · Arena Elo 1375)
  • Hohe Generierungsgeschwindigkeit von 240 Token/Sekunde bei nur 290 ms Erstlatenz (TTFT)
  • Effiziente API-Struktur ($0.4/$2 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.

MetricGemini 3.6 FlashGemini 3.5 Flash-Lite
Cost per Task
Estimated USD to finish one task
$1.02$0.55
Output Tokens / Task
Tokens generated per task
39K18K
Reasoning Tokens / Task
Thinking tokens burned per task
19K7K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 3.6 FlashGemini 3.5 Flash-Lite
Official API Model ID (SDK)models/gemini-3-6-flashmodels/gemini-3-5-flash-lite
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-072026-07
Knowledge CutoffMarch 2026March 2026
ArchitectureEnhanced multimodal mixture-of-expertsLightweight efficient multimodal transformer
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 $0.1875/1M with configurable TTLImplicit + Explicit Context Caching at $0.1/1M 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 3.6 Flash vs Gemini 3.5 Flash-Lite: Schnelle Antworten (FAQ)

Which is more intelligent, Gemini 3.6 Flash or Gemini 3.5 Flash-Lite?

Gemini 3.6 Flash is more intelligent. It scores 84 compared with 69 on the composite Intelligence Index.

Which model is faster?

Gemini 3.5 Flash-Lite is faster, generating 240 tokens per second compared with 185 tokens per second.

Which model is cheaper to run?

Gemini 3.5 Flash-Lite is cheaper at $0.35 per 1M tokens blended, compared with $0.66 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3.5 Flash-Lite has lower latency, with a time to first token of 0.29s compared with 0.37s.

Fazit

Sowohl Gemini 3.6 Flash (Optimal für autonomes Software-Engineering, Code-Refactoring und komplexe Fehleranalyse, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Gemini 3.5 Flash-Lite (Optimal für ultraschnelle Echtzeit-Antworten, niedrige Latenz und Hochdurchsatz-Routing, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Gemini 3.6 Flash führt bei komplexem Reasoning und Coding, Gemini 3.5 Flash-Lite liefert den höheren Token-Durchsatz und Gemini 3.5 Flash-Lite ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Gemini 3.6 Flash oder Gemini 3.5 Flash-Lite?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Gemini 3.6 Flash vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Gemini 3.6 Flash und Gemini 3.5 Flash-Lite?+

Gemini 3.6 Flash kostet $0.75 / $3.75 pro 1M Input-/Output-Tokens, Gemini 3.5 Flash-Lite liegt bei $0.40 / $2.00. Beim gewichteten Gesamtpreis ist Gemini 3.5 Flash-Lite günstiger.

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

Gemini 3.6 Flash bietet 1.05M Tokens Kontext gegenüber 1.05M Tokens bei Gemini 3.5 Flash-Lite. Bei der Generierungsgeschwindigkeit liegt Gemini 3.5 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 & 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.

Offizielle Quellen: Offizielle API-Dokumentation von Google und Google, Systemkarten und unabhängige Benchmark-Auswertungen (2026).