Head-to-Head Model Comparison

Gemini 3.8 Flash vs Gemini 3.5 Flash

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 3.8 FlashProfile

Gemini 3.5 FlashProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

Google

Gemini 3.8 Flash

Inferensi Super Cepat

Gemini 3.8 Flash dari Google adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 1.0M, kecepatan 175 token/detik, indeks kecerdasan 87/100, serta t

Intelligence Index87 / 100

Input Token:

$0.75 / 1M

Output Token:

$3.75 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

74.8%

Google

Gemini 3.5 Flash

Model Unggulan Garis Depan

Gemini 3.5 Flash dari Google adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1.0M, kecepatan 190 token/detik, indeks kecerdasan 82/100, serta t

Intelligence Index82 / 100

Input Token:

$0.75 / 1M

Output Token:

$3.75 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

70.2%

Perbedaan Utama Sekilas

Both models cost the same under this workload — choose on capability, not price.
Gemini 3.5 Flash is faster at 190 tok/s vs 175 tok/s.
Gemini 3.8 Flash leads on SWE-bench coding (74.8% vs 70.2%).

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

Feature	Gemini 3.8 Flash	Gemini 3.5 Flash
Intelligence Index Composite reasoning & knowledge score (0-100)	87	82
Provider	Google	Google
Input Price Cost per million input tokens	$0.75 / 1M	$0.75 / 1M
Output Price Cost per million output tokens	$3.75 / 1M	$3.75 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.66 / 1M	$0.66 / 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	66K	66K
Throughput Speed Tokens generated per second	175 tok/s	190 tok/s
SWE-bench Verified Real-world software engineering	74.8%	70.2%
GPQA Diamond Graduate-level reasoning	84%	81%
Cached Input Price Prompt caching discount per 1M tokens	$0.19 / 1M	$0.19 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

Gemini 3.8 Flash

+4.6% SWE-bench lead

Cost

Tied

Identical monthly runtime cost

Speed

Gemini 3.5 Flash

+9% faster generation

Context

Tied

1.05M tokens window

Skor Benchmark Terverifikasi

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

Gemini 3.8 FlashGemini 3.5 Flash

SWE-bench Verified (Autonomous Coding)

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

74.8%vs70.2%

GPQA Diamond (Doctorate-Level Science & Math)

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

84%vs81%

MMLU-Pro (Multi-task Language Understanding)

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

88.8%vs87.1%

LMSYS Chatbot Arena Elo

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

1480ptsvs1450pts

AIME (Advanced Math Competition)

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

89.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

175 tok/s vs190 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 3.8 Flash0.39s

Gemini 3.5 Flash0.36s

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

Gemini 3.8 Flash3.25s

Gemini 3.5 Flash2.99s

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 3.8 Flash Monthly API Bill

$4.78 / month

$0.75/1M in · $3.75/1M out

Gemini 3.5 Flash Monthly API Bill

$4.78 / month

$0.75/1M in · $3.75/1M out

These models cost the same under this workload — no savings either way.Break-even

Gemini 3.8 Flash · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 74.8% · GPQA Diamond 84%)
Kecepatan generasi tinggi 175 token/detik dengan latensi token pertama (TTFT) hanya 390 ms
Skema harga API kompetitif (tarif $0.75/$3.75 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 3.5 Flash · Strengths & Key Advantages

Jendela konteks 1.0M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 70.2% · GPQA Diamond 81%)
Kecepatan generasi tinggi 190 token/detik dengan latensi token pertama (TTFT) hanya 360 ms
Skema harga API kompetitif (tarif $0.75/$3.75 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 3.8 Flash	Gemini 3.5 Flash
Cost per Task Estimated USD to finish one task	$1.20	$1.05
Output Tokens / Task Tokens generated per task	44K	38K
Reasoning Tokens / Task Thinking tokens burned per task	21K	18K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Gemini 3.8 Flash vs Gemini 3.5 Flash: Jawaban Cepat (FAQ)

Which is more intelligent, Gemini 3.8 Flash or Gemini 3.5 Flash?

Gemini 3.8 Flash is more intelligent. It scores 87 compared with 82 on the composite Intelligence Index.

Which model is faster?

Gemini 3.5 Flash is faster, generating 190 tokens per second compared with 175 tokens per second.

Which model has lower latency?

Gemini 3.5 Flash has lower latency, with a time to first token of 0.36s compared with 0.39s.

Kesimpulan

Baik Gemini 3.8 Flash (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 3.5 Flash (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 3.8 Flash unggul dalam penalaran dan pemrograman, Gemini 3.5 Flash memberikan kecepatan generasi token lebih tinggi, dan Gemini 3.8 Flash lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Gemini 3.8 Flash atau Gemini 3.5 Flash?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 3.8 Flash memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Gemini 3.8 Flash vs Gemini 3.5 Flash?+

Gemini 3.8 Flash mengenakan biaya $0.75 / $3.75 per 1M token input/output, sedangkan Gemini 3.5 Flash sebesar $0.75 / $3.75. Secara keseluruhan, Gemini 3.8 Flash lebih hemat biaya.

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

Gemini 3.8 Flash mendukung konteks 1.05M token dibandingkan 1.05M token pada Gemini 3.5 Flash, sementara Gemini 3.5 Flash 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 3.8 Flash	Gemini 3.5 Flash
Official API Model ID (SDK)	models/gemini-3-8-flash	models/gemini-3-5-flash
API Protocol	Google Gemini API (generateContent) + OpenAI-Compatible SDK	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2026-09	2026-05
Knowledge Cutoff	June 2026	January 2026
Architecture	Late-2026 optimized sparse multimodal transformer	Optimized Search-Grade Multimodal MoE
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 $0.1875/1M with configurable TTL	Implicit + Explicit Context Caching at $0.1875/1M 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) · 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 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, audio, video	text, vision, audio, video
Output Modalities	text	text

Gemini 3.8 Flash vs Gemini 3.5 Flash

Ganti & Bandingkan Model Apa Saja

Gemini 3.8 Flash

Gemini 3.5 Flash

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

Gemini 3.8 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 3.5 Flash · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

Gemini 3.8 Flash vs Gemini 3.5 Flash: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

Related reading