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Head-to-Head Model Comparison

Gemini 2.0 Flash-Lite vs Gemini 1.5 Flash-8B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

GetInfoUs araştırma ekibi tarafından incelendiSon inceleme: October 2026Yayın ilkeleri
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Gemini 2.0 Flash-Lite vs Gemini 1.5 Flash-8B: Benchmarks, Pricing & Speed Comparison

Google tarafından geliştirilen Gemini 2.0 Flash-Lite ve Google tarafından sunulan Gemini 1.5 Flash-8B, kendi sınıflarının öne çıkan yapay zeka modelleridir. Gemini 2.0 Flash-Lite, 1.05M token bağlam penceresi ve 1M token başına $0.07/$0.30 fiyat sunarken; Gemini 1.5 Flash-8B, 1.05M token bağlam penceresi ve $0.04/$0.15 fiyatla gelir. Aşağıda tüm benchmark, hız ve maliyet detaylarını inceleyebilirsiniz.

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Google

Gemini 2.0 Flash-Lite

Hafif ve Ekonomik Model

Google tarafından geliştirilen Gemini 2.0 Flash-Lite; token başına maksimum maliyet verimliliği ve hızlı üretim çıkarımı için tasarlanmış olup 1.0M bağlam penceresi, 280 token/sn hız, 48/100 zeka indeksi ve 1M token başına $0.075/$0.3 fiyat

Intelligence Index48 / 100
Input Token:

$0.07 / 1M

Output Token:

$0.30 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

N/A

Google

Gemini 1.5 Flash-8B

Yerel Çok Modlu Yapay Zeka

Google tarafından geliştirilen Gemini 1.5 Flash-8B; yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi için tasarlanmış olup 1.0M bağlam penceresi, 160 token/sn hız, 37/100 zeka indeksi ve 1M token başına $0.0375/$0.15 fiyatl

Intelligence Index37 / 100
Input Token:

$0.04 / 1M

Output Token:

$0.15 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

24.5%

Bir Bakışta Temel Farklar

  • Gemini 1.5 Flash-8B is 2.0x cheaper for API usage (input + output tokens combined).
  • Gemini 2.0 Flash-Lite is faster at 280 tok/s vs 160 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.0 Flash-LiteGemini 1.5 Flash-8B
Intelligence Index
Composite reasoning & knowledge score (0-100)
4837
Provider
GoogleGoogle
Input Price
Cost per million input tokens
$0.07 / 1M$0.04 / 1M
Output Price
Cost per million output tokens
$0.30 / 1M$0.15 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.06 / 1M$0.03 / 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
8K8K
Throughput Speed
Tokens generated per second
280 tok/s160 tok/s
SWE-bench Verified
Real-world software engineering
N/A24.5%
GPQA Diamond
Graduate-level reasoning
N/A38.2%
Cached Input Price
Prompt caching discount per 1M tokens
$0.02 / 1M$0.01 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Gemini 1.5 Flash-8B
2.0x cheaper monthly runtime
Speed
Gemini 2.0 Flash-Lite
+75% faster generation
Context
Tied
1.05M tokens window

Doğrulanmış Benchmark Puanları

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

Gemini 2.0 Flash-LiteGemini 1.5 Flash-8B
SWE-bench Verified (Autonomous Coding)

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

N/Avs24.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs38.2%
MMLU-Pro (Multi-task Language Understanding)

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

72.5%vs58.6%
LMSYS Chatbot Arena Elo

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

1305ptsvs1220pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

N/Avs3.5%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs16.5%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

N/Avs17.8%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs31.4%
AIME (Advanced Math Competition)

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

N/Avs34.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

N/Avs69.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

280 tok/s vs160 tok/s

Gecikme Süresi ve Yanıt Hızı

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 2.0 Flash-Lite0.29s
Gemini 1.5 Flash-8B0.25s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.0 Flash-Lite2.08s
Gemini 1.5 Flash-8B3.38s

Gerçek Zamanlı Token Maliyet Simülatörü

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 2.0 Flash-Lite Monthly API Bill
$0.41 / month
$0.075/1M in · $0.3/1M out
Gemini 1.5 Flash-8B Monthly API Bill
$0.21 / month
$0.0375/1M in · $0.15/1M out
Gemini 1.5 Flash-8B saves approximately $0.20 / month (50%) under this workload.2.0x Savings

Gemini 2.0 Flash-Lite · Strengths & Key Advantages

  • 1.0M bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (MMLU-Pro 72.5% · Arena Elo 1305)
  • Sadece 290 ms ilk token gecikmesi (TTFT) ile saniyede 280 token yüksek üretim hızı
  • İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $0.075/$0.3 fiyatlandırma)
Considerations & Trade-offs
  • Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Gemini 1.5 Flash-8B · Strengths & Key Advantages

  • 1.0M bağlam penceresi ve yanıt başına maksimum 8K çıktı tokenı kapasitesi (SWE-bench Verified 24.5% · GPQA Diamond 38.2%)
  • Sadece 250 ms ilk token gecikmesi (TTFT) ile saniyede 160 token yüksek üretim hızı
  • İstem önbellekleme (Prompt Caching), araç çağırma ve yapılandırılmış JSON çıktısını destekleyen rekabetçi API ekonomisi (1M token başına $0.0375/$0.15 fiyatlandırma)
Considerations & Trade-offs
  • Kapalı ağırlıklı bulut modelidir; çevrimdışı yerel sunuculara indirilerek çalıştırılamaz
  • Çok karmaşık akademik ve bilimsel çıkarımlarda üst düzey ağır akıl yürütme modelleri daha derin sonuçlar verebilir

Token Use & Task Economics

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

MetricGemini 2.0 Flash-LiteGemini 1.5 Flash-8B
Cost per Task
Estimated USD to finish one task
$0.25$0.04
Output Tokens / Task
Tokens generated per task
6K18K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.0 Flash-LiteGemini 1.5 Flash-8B
Official API Model ID (SDK)models/gemini-2-0-flash-litemodels/gemini-1-5-flash-8b
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKGoogle Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2025-022024-10
Knowledge CutoffAugust 2024May 2024
ArchitectureDistilled lightweight multimodal transformerHigh-Throughput Multimodal Transformer
ParametersConfidential8B
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 $0.01875/1M with configurable TTLImplicit + Explicit Context Caching at $0.01/1M 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) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
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, audio, video
Output Modalitiestexttext

Gemini 2.0 Flash-Lite vs Gemini 1.5 Flash-8B: Hızlı Yanıtlar (SSS)

Which is more intelligent, Gemini 2.0 Flash-Lite or Gemini 1.5 Flash-8B?

Gemini 2.0 Flash-Lite is more intelligent. It scores 48 compared with 37 on the composite Intelligence Index.

Which model is faster?

Gemini 2.0 Flash-Lite is faster, generating 280 tokens per second compared with 160 tokens per second.

Which model is cheaper to run?

Gemini 1.5 Flash-8B is cheaper at $0.03 per 1M tokens blended, compared with $0.06 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Gemini 1.5 Flash-8B has lower latency, with a time to first token of 0.25s compared with 0.29s.

Sonuç

Hem Gemini 2.0 Flash-Lite (token başına maksimum maliyet verimliliği ve hızlı üretim çıkarımı, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) hem de Gemini 1.5 Flash-8B (yerel çok modlu metin ve görsel anlama ile karmaşık belge analizi, kurumsal RAG mimarileri ve ölçeklenebilir üretim API entegrasyonları için idealdir.) güçlü üretim seçenekleridir: Gemini 2.0 Flash-Lite karmaşık akıl yürütme ve kodlama testlerinde öne çıkarken, Gemini 2.0 Flash-Lite daha yüksek üretim hızı sağlar; Gemini 1.5 Flash-8B ise yüksek hacimli API kullanımlarında daha ekonomiktir.

Sıkça Sorulan Sorular (SSS)

Kodlama ve akıl yürütme için Gemini 2.0 Flash-Lite mi yoksa Gemini 1.5 Flash-8B mi daha iyi?+

Bileşik zeka endeksi ve yazılım testlerinde Gemini 2.0 Flash-Lite önde yer alıyor. Detaylı karşılaştırma için yukarıdaki SWE-bench ve GPQA tablolarına göz atabilirsiniz.

Gemini 2.0 Flash-Lite ve Gemini 1.5 Flash-8B API fiyatları nasıl karşılaştırılır?+

Gemini 2.0 Flash-Lite 1M giriş/çıkış tokeni başına $0.07 / $0.30 ücretlendirilirken, Gemini 1.5 Flash-8B $0.04 / $0.15 seviyesindedir. Karma maliyette Gemini 1.5 Flash-8B daha avantajlıdır.

Hangi modelin bağlam penceresi daha geniş ve hızı daha yüksek?+

Gemini 2.0 Flash-Lite 1.05M token bağlam penceresi sunarken Gemini 1.5 Flash-8B 1.05M token kapasiteye sahiptir. Saniyedeki token üretim hızında ise Gemini 2.0 Flash-Lite öndedir.

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.

Resmi kaynaklar: Google ve Google resmi API dokümantasyonu, sistem kartları ve bağımsız benchmark testleri (2026).