Head-to-Head Model Comparison

GPT-4o vs Gemini 1.5 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial

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

GPT-4oProfile

Gemini 1.5 ProProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-4o

Model Suara & Audio Asli

GPT-4o dari OpenAI adalah model AI yang dirancang untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, menghadirkan jendela konteks 128K, kecepatan 105 token/detik, indeks kecerdasan 41/100, serta tarif $2.5/$10 p

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Google

Gemini 1.5 Pro

Model Generasi Klasik

Gemini 1.5 Pro dari Google adalah model AI yang dirancang untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, menghadirkan jendela konteks 2M, kecepatan 65 token/detik, indeks kecerdasan 46/100, serta tarif $1.25/$5

Intelligence Index46 / 100

Input Token:

$1.25 / 1M

Output Token:

$5.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

32.5%

Perbedaan Utama Sekilas

Gemini 1.5 Pro is 2.1x cheaper for API usage (input + output tokens combined).
Gemini 1.5 Pro has a larger context window (2M vs 128K tokens).
GPT-4o is faster at 105 tok/s vs 65 tok/s.
GPT-4o leads on SWE-bench coding (38.8% vs 32.5%).

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

Feature	GPT-4o	Gemini 1.5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	41	46
Provider	OpenAI	Google
Input Price Cost per million input tokens	$2.50 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$10.00 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.38 / 1M	$0.97 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	2M tokens~3,000 A4 pages of text
Max Output Tokens Per single request	16K	8K
Throughput Speed Tokens generated per second	105 tok/s	65 tok/s
SWE-bench Verified Real-world software engineering	38.8%	32.5%
GPQA Diamond Graduate-level reasoning	53.6%	58.5%
Cached Input Price Prompt caching discount per 1M tokens	$1.25 / 1M	$0.31 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework

Coding

GPT-4o

+6.3% SWE-bench lead

Cost

Gemini 1.5 Pro

2.1x cheaper monthly runtime

Speed

GPT-4o

+62% faster generation

Context

Gemini 1.5 Pro

2M tokens window

Skor Benchmark Terverifikasi

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

GPT-4oGemini 1.5 Pro

SWE-bench Verified (Autonomous Coding)

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

38.8%vs32.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

53.6%vs58.5%

MMLU-Pro (Multi-task Language Understanding)

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

72.6%vs75.2%

LMSYS Chatbot Arena Elo

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

1286ptsvs1290pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

4.1%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

18.5%vsN/A

SciCode (Scientific Computing)

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

27.3%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.9%vsN/A

AIME (Advanced Math Competition)

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

29.7%vsN/A

Long-Context Reasoning

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

58.2%vs89.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs65 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

GPT-4o0.41s

Gemini 1.5 Pro0.80s

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

GPT-4o5.17s

Gemini 1.5 Pro8.49s

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)

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

Gemini 1.5 Pro Monthly API Bill

$6.84 / month

$1.25/1M in · $5/1M out

Gemini 1.5 Pro saves approximately $7.79 / month (53%) under this workload.2.1x Savings

GPT-4o · Strengths & Key Advantages

Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Kecepatan generasi tinggi 105 token/detik dengan latensi token pertama (TTFT) hanya 410 ms
Skema harga API kompetitif (tarif $2.5/$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
Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Gemini 1.5 Pro · Strengths & Key Advantages

Jendela konteks 2M dengan kapasitas output maksimum hingga 8K token (SWE-bench Verified 32.5% · GPQA Diamond 58.5%)
Kecepatan generasi tinggi 65 token/detik dengan latensi token pertama (TTFT) hanya 800 ms
Skema harga API kompetitif (tarif $1.25/$5 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	GPT-4o	Gemini 1.5 Pro
Cost per Task Estimated USD to finish one task	$0.68	$0.20
Output Tokens / Task Tokens generated per task	24K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-4o	Gemini 1.5 Pro
Official API Model ID (SDK)	gpt-4o	models/gemini-1-5-pro
API Protocol	OpenAI Responses API & Chat Completions v1	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2024-05	2024-02
Knowledge Cutoff	October 2023	May 2024
Architecture	Omni-Multimodal Dense	Sparse Mixture-of-Experts (MoE) Multimodal
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($2.5/1M in) across full 128K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $1.25/1M (no extra cache-write fee)	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	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	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)	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	OpenAI Preparedness Framework Audited & System Card Published	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	text, vision, audio, video
Output Modalities	text, audio	text

GPT-4o vs Gemini 1.5 Pro: Jawaban Cepat (FAQ)

Which is more intelligent, GPT-4o or Gemini 1.5 Pro?

Gemini 1.5 Pro is more intelligent. It scores 46 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Gemini 1.5 Pro is cheaper at $0.97 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.80s.

Which model has a larger context window?

Gemini 1.5 Pro has a larger context window, supporting 2M tokens compared with 128K tokens.

Kesimpulan

Baik GPT-4o (Sangat cocok untuk sintesis suara alami, pemrosesan audio real-time, dan transkripsi ucapan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Gemini 1.5 Pro (Sangat cocok untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Gemini 1.5 Pro unggul dalam penalaran dan pemrograman, GPT-4o memberikan kecepatan generasi token lebih tinggi, dan Gemini 1.5 Pro lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GPT-4o atau Gemini 1.5 Pro?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 1.5 Pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GPT-4o vs Gemini 1.5 Pro?+

GPT-4o mengenakan biaya $2.50 / $10.00 per 1M token input/output, sedangkan Gemini 1.5 Pro sebesar $1.25 / $5.00. Secara keseluruhan, Gemini 1.5 Pro lebih hemat biaya.

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

GPT-4o mendukung konteks 128K token dibandingkan 2M token pada Gemini 1.5 Pro, sementara GPT-4o 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)

GPT-4o vs Gemini 1.5 Pro

Ganti & Bandingkan Model Apa Saja

GPT-4o

Gemini 1.5 Pro

Siapa Unggul di Mana?

Skor Benchmark Terverifikasi

Latensi & Waktu Respons

Simulator Biaya Token Interaktif

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 1.5 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Spesifikasi Teknis

GPT-4o vs Gemini 1.5 Pro: Jawaban Cepat (FAQ)

Kesimpulan

Pertanyaan Umum (FAQ)

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