Head-to-Head Model Comparison

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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Claude Sonnet 4.6Profile

Gemini 3.1 Flash-LiteProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Anthropic

Claude Sonnet 4.6

Model Unggulan Garis Depan

Claude Sonnet 4.6 dari Anthropic adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 92 token/detik, indeks kecerdasan 60/100, serta

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

Model Ringan & Hemat Biaya

Gemini 3.1 Flash-Lite dari Google adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 1.0M, kecepatan 250 token/detik, indeks kecerdasan 60/100, serta

Intelligence Index60 / 100

Input Token:

$0.15 / 1M

Output Token:

$0.60 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Perbedaan Utama Sekilas

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

Siapa Unggul di Mana?

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

Skor Benchmark Terverifikasi

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

Latensi & Waktu Respons

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

Simulator Biaya Token Interaktif

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

Jendela konteks 1M dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 76.1% · GPQA Diamond 74%)
Kecepatan generasi tinggi 92 token/detik dengan latensi token pertama (TTFT) hanya 650 ms
Skema harga API kompetitif (tarif $3/$15 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Gemini 3.1 Flash-Lite · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 33K token (MMLU-Pro 78.5% · Arena Elo 1355)
Kecepatan generasi tinggi 250 token/detik dengan latensi token pertama (TTFT) hanya 270 ms
Skema harga API kompetitif (tarif $0.15/$0.6 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur

Considerations & Trade-offs

Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

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

Spesifikasi Teknis

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: Jawaban Cepat (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.

Kesimpulan

Baik Claude Sonnet 4.6 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 3.1 Flash-Lite (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Claude Sonnet 4.6 unggul dalam penalaran dan pemrograman, Gemini 3.1 Flash-Lite memberikan kecepatan generasi token lebih tinggi, dan Gemini 3.1 Flash-Lite lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Claude Sonnet 4.6 atau Gemini 3.1 Flash-Lite?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Claude Sonnet 4.6 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite?+

Claude Sonnet 4.6 mengenakan biaya $3.00 / $15.00 per 1M token input/output, sedangkan Gemini 3.1 Flash-Lite sebesar $0.15 / $0.60. Secara keseluruhan, Gemini 3.1 Flash-Lite lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Claude Sonnet 4.6 mendukung konteks 1M token dibandingkan 1.05M token pada Gemini 3.1 Flash-Lite, sementara Gemini 3.1 Flash-Lite unggul dalam kecepatan output token per detik.

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

Ganti & Bandingkan Model Apa Saja

Claude Sonnet 4.6

Gemini 3.1 Flash-Lite

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

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

Spesifikasi Teknis

Claude Sonnet 4.6 vs Gemini 3.1 Flash-Lite: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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