Head-to-Head Model Comparison

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Geprüft vom GetInfoUs-ForschungsteamZuletzt geprüft: October 2026Redaktionelle Richtlinien

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Claude Sonnet 4.6Profile

Gemini 3.1 Flash-LiteProfile

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Popular Matchups:

Anthropic

Claude Sonnet 4.6

Frontier-Flaggschiff-Modell

Claude Sonnet 4.6 von Anthropic ist ein KI-Modell für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows mit 1M Kontextfenster, 92 Token/s Durchsatz, einem Intelligenz-Index von 60/100 und $3/$15 pro 1M To

Intelligence Index60 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.1%

Google

Gemini 3.1 Flash-Lite

Kompaktes Effizienz-Modell

Gemini 3.1 Flash-Lite von Google ist ein KI-Modell für maximale Kosteneffizienz pro Token und ressourcenschonende Produktions-Workloads mit 1.0M Kontextfenster, 250 Token/s Durchsatz, einem Intelligenz-Index von 60/100 und $0.15/$0.6 pro 1M

Intelligence Index60 / 100

Input Token:

$0.15 / 1M

Output Token:

$0.60 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Wichtigste Unterschiede auf einen Blick

Gemini 3.1 Flash-Lite is 22.6x cheaper for API usage (input + output tokens combined).
Gemini 3.1 Flash-Lite has a larger context window (1M vs 1M tokens).
Gemini 3.1 Flash-Lite is faster at 250 tok/s vs 92 tok/s.

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Claude Sonnet 4.6	Gemini 3.1 Flash-Lite
Intelligence Index Composite reasoning & knowledge score (0-100)	60	60
Provider	Anthropic	Google
Input Price Cost per million input tokens	$3.00 / 1M	$0.15 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$0.60 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.31 / 1M	$0.11 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	1.05M tokens~1,573 A4 pages of text
Max Output Tokens Per single request	128K	33K
Throughput Speed Tokens generated per second	92 tok/s	250 tok/s
SWE-bench Verified Real-world software engineering	76.1%	N/A
GPQA Diamond Graduate-level reasoning	74%	N/A
Cached Input Price Prompt caching discount per 1M tokens	$0.30 / 1M	$0.04 / 1M

Wer gewinnt in welcher Disziplin?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Gemini 3.1 Flash-Lite

22.6x cheaper monthly runtime

Speed

Gemini 3.1 Flash-Lite

+172% faster generation

Context

Gemini 3.1 Flash-Lite

1.05M tokens window

Geprüfte Benchmark-Ergebnisse im Vergleich

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

Claude Sonnet 4.6Gemini 3.1 Flash-Lite

SWE-bench Verified (Autonomous Coding)

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

76.1%vsN/A

GPQA Diamond (Doctorate-Level Science & Math)

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

74%vsN/A

MMLU-Pro (Multi-task Language Understanding)

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

86.7%vs78.5%

LMSYS Chatbot Arena Elo

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

1380ptsvs1355pts

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

47.8%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

92 tok/s vs250 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

Claude Sonnet 4.60.65s

Gemini 3.1 Flash-Lite0.27s

Est. End-to-End Response (500 tokens)TTFT + generation time

Claude Sonnet 4.66.08s

Gemini 3.1 Flash-Lite2.27s

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)

Claude Sonnet 4.6 Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Gemini 3.1 Flash-Lite Monthly API Bill

$0.82 / month

$0.15/1M in · $0.6/1M out

Gemini 3.1 Flash-Lite saves approximately $17.63 / month (96%) under this workload.22.6x Savings

Claude Sonnet 4.6 · Strengths & Key Advantages

1M Kontextfenster und bis zu 128K maximale Output-Token (SWE-bench Verified 76.1% · GPQA Diamond 74%)
Hohe Generierungsgeschwindigkeit von 92 Token/Sekunde bei nur 650 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($3/$15 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 hohem Anfragevolumen empfiehlt sich der Einsatz von Prompt-Caching und Batch-API zur Kostenoptimierung

Gemini 3.1 Flash-Lite · Strengths & Key Advantages

1.0M Kontextfenster und bis zu 33K maximale Output-Token (MMLU-Pro 78.5% · Arena Elo 1355)
Hohe Generierungsgeschwindigkeit von 250 Token/Sekunde bei nur 270 ms Erstlatenz (TTFT)
Effiziente API-Struktur ($0.15/$0.6 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	Claude Sonnet 4.6	Gemini 3.1 Flash-Lite
Cost per Task Estimated USD to finish one task	$3.29	$0.38
Output Tokens / Task Tokens generated per task	72K	14K
Reasoning Tokens / Task Thinking tokens burned per task	37K	5K

Technische Spezifikationen

Architecture, release timeline, capabilities, and modalities.

Feature	Claude Sonnet 4.6	Gemini 3.1 Flash-Lite
Official API Model ID (SDK)	claude-sonnet-4-6-20260201	models/gemini-3-1-flash-lite
API Protocol	Anthropic Messages API + AWS Bedrock + Vertex AI	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2026-02	2026-03
Knowledge Cutoff	December 2025	November 2025
Architecture	High-Throughput Multimodal Agent Transformer	Compact efficient multimodal transformer
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 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	$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL	Implicit + Explicit Context Caching at $0.035/1M 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	Native Web Search Citations + Code Execution Tool + MCP Connectors	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Custom Model Tuning via Amazon Bedrock & Prompt Distillation	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated	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	text, vision
Output Modalities	text	text

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite: Schnelle Antworten (FAQ)

Which model is faster?

Gemini 3.1 Flash-Lite is faster, generating 250 tokens per second compared with 92 tokens per second.

Which model is cheaper to run?

Gemini 3.1 Flash-Lite is cheaper at $0.11 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 3.1 Flash-Lite has lower latency, with a time to first token of 0.27s compared with 0.65s.

Which model has a larger context window?

Gemini 3.1 Flash-Lite has a larger context window, supporting 1.05M tokens compared with 1M tokens.

Fazit

Sowohl Claude Sonnet 4.6 (Optimal für anspruchsvolles Enterprise-Reasoning, Softwareentwicklung und produktive KI-Workflows, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) als auch Gemini 3.1 Flash-Lite (Optimal für maximale Kosteneffizienz pro Token und ressourcenschonende Produktions-Workloads, Enterprise-RAG-Systeme und skalierbare API-Pipelines.) überzeugen im Produktionseinsatz: Claude Sonnet 4.6 führt bei komplexem Reasoning und Coding, Gemini 3.1 Flash-Lite liefert den höheren Token-Durchsatz und Gemini 3.1 Flash-Lite ist die kosteneffizienteste Wahl für große API-Workloads.

Häufig gestellte Fragen (FAQ)

Welches Modell ist besser für Coding und Reasoning – Claude Sonnet 4.6 oder Gemini 3.1 Flash-Lite?+

Im Gesamt-Intelligenzindex und bei Software-Benchmarks liegt Claude Sonnet 4.6 vorn. Prüfen Sie oben die SWE-bench- und GPQA-Werte für Ihren Anwendungsfall.

Wie unterscheiden sich die API-Preise von Claude Sonnet 4.6 und Gemini 3.1 Flash-Lite?+

Claude Sonnet 4.6 kostet $3.00 / $15.00 pro 1M Input-/Output-Tokens, Gemini 3.1 Flash-Lite liegt bei $0.15 / $0.60. Beim gewichteten Gesamtpreis ist Gemini 3.1 Flash-Lite günstiger.

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

Claude Sonnet 4.6 bietet 1M Tokens Kontext gegenüber 1.05M Tokens bei Gemini 3.1 Flash-Lite. Bei der Generierungsgeschwindigkeit liegt Gemini 3.1 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)

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite

Beliebige Modelle wechseln & vergleichen

Claude Sonnet 4.6

Gemini 3.1 Flash-Lite

Wer gewinnt in welcher Disziplin?

Geprüfte Benchmark-Ergebnisse im Vergleich

Latenz & Antwortzeit

Interaktiver Token-Kosten-Simulator

Claude Sonnet 4.6 · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3.1 Flash-Lite · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Technische Spezifikationen

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite: Schnelle Antworten (FAQ)

Fazit

Häufig gestellte Fragen (FAQ)

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