Head-to-Head Model Comparison

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

Ganti & Bandingkan Model Apa Saja

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Gemini 2.5 Flash-LiteProfile

Gemini 2.5 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 2.5 Flash-Lite

Model Ringan & Hemat Biaya

Gemini 2.5 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 220 token/detik, indeks kecerdasan 56/100, serta

Intelligence Index56 / 100

Input Token:

$0.10 / 1M

Output Token:

$0.40 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Google

Gemini 2.5 Pro

Mesin Penalaran Mendalam

Gemini 2.5 Pro dari Google adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 1.0M, kecepatan 95 token/detik, indeks kecerdasan 78/100, serta tarif $1.

Intelligence Index78 / 100

Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

63.8%

Perbedaan Utama Sekilas

Gemini 2.5 Flash-Lite is 20.7x cheaper for API usage (input + output tokens combined).
Gemini 2.5 Flash-Lite is faster at 220 tok/s vs 95 tok/s.

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

Feature	Gemini 2.5 Flash-Lite	Gemini 2.5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	56	78
Provider	Google	Google
Input Price Cost per million input tokens	$0.10 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$0.40 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.08 / 1M	$1.47 / 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	33K	66K
Throughput Speed Tokens generated per second	220 tok/s	95 tok/s
SWE-bench Verified Real-world software engineering	N/A	63.8%
GPQA Diamond Graduate-level reasoning	N/A	84%
Cached Input Price Prompt caching discount per 1M tokens	$0.03 / 1M	$0.31 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Evaluations ongoing

Cost

Gemini 2.5 Flash-Lite

20.7x cheaper monthly runtime

Speed

Gemini 2.5 Flash-Lite

+132% faster generation

Context

Tied

1.05M tokens window

Skor Benchmark Terverifikasi

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

Gemini 2.5 Flash-LiteGemini 2.5 Pro

SWE-bench Verified (Autonomous Coding)

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

N/Avs63.8%

GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs84%

MMLU-Pro (Multi-task Language Understanding)

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

76.5%vs88.5%

LMSYS Chatbot Arena Elo

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

1330ptsvs1420pts

AIME (Advanced Math Competition)

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

N/Avs92%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

220 tok/s vs95 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

Gemini 2.5 Flash-Lite0.32s

Gemini 2.5 Pro0.82s

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

Gemini 2.5 Flash-Lite2.59s

Gemini 2.5 Pro6.08s

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)

Gemini 2.5 Flash-Lite Monthly API Bill

$0.55 / month

$0.1/1M in · $0.4/1M out

Gemini 2.5 Pro Monthly API Bill

$11.34 / month

$1.25/1M in · $10/1M out

Gemini 2.5 Flash-Lite saves approximately $10.79 / month (95%) under this workload.20.7x Savings

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 33K token (MMLU-Pro 76.5% · Arena Elo 1330)
Kecepatan generasi tinggi 220 token/detik dengan latensi token pertama (TTFT) hanya 320 ms
Skema harga API kompetitif (tarif $0.1/$0.4 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

Gemini 2.5 Pro · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 63.8% · GPQA Diamond 84%)
Kecepatan generasi tinggi 95 token/detik dengan latensi token pertama (TTFT) hanya 820 ms
Skema harga API kompetitif (tarif $1.25/$10 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	Gemini 2.5 Flash-Lite	Gemini 2.5 Pro
Cost per Task Estimated USD to finish one task	$0.35	$1.45
Output Tokens / Task Tokens generated per task	12K	45K
Reasoning Tokens / Task Thinking tokens burned per task	4K	22K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro: Jawaban Cepat (FAQ)

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

Gemini 2.5 Pro is more intelligent. It scores 78 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 95 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 $1.47 (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 0.82s.

Kesimpulan

Baik Gemini 2.5 Flash-Lite (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 2.5 Pro (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 2.5 Pro unggul dalam penalaran dan pemrograman, Gemini 2.5 Flash-Lite memberikan kecepatan generasi token lebih tinggi, dan Gemini 2.5 Flash-Lite lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Gemini 2.5 Flash-Lite atau Gemini 2.5 Pro?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 2.5 Pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro?+

Gemini 2.5 Flash-Lite mengenakan biaya $0.10 / $0.40 per 1M token input/output, sedangkan Gemini 2.5 Pro sebesar $1.25 / $10.00. Secara keseluruhan, Gemini 2.5 Flash-Lite lebih hemat biaya.

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

Gemini 2.5 Flash-Lite mendukung konteks 1.05M token dibandingkan 1.05M token pada Gemini 2.5 Pro, sementara Gemini 2.5 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)

Feature	Gemini 2.5 Flash-Lite	Gemini 2.5 Pro
Official API Model ID (SDK)	models/gemini-2-5-flash-lite	models/gemini-2-5-pro
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2025-06	2025-03
Knowledge Cutoff	March 2025	January 2025
Architecture	Compact multimodal transformer with lightweight thinking	Pathways Multimodal Sparse Mixture-of-Experts with 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 $0.025/1M with configurable TTL	Implicit + Explicit Context Caching at $0.31/1M 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)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
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	text, vision, audio, video
Output Modalities	text	text

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro

Ganti & Bandingkan Model Apa Saja

Gemini 2.5 Flash-Lite

Gemini 2.5 Pro

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Gemini 2.5 Flash-Lite · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 2.5 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Gemini 2.5 Flash-Lite vs Gemini 2.5 Pro: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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