Gemini 3 Pro vs GPT-5 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Gemini 3 Pro dari Google dan GPT-5 Pro dari OpenAI adalah dua model AI unggulan. Gemini 3 Pro menawarkan jendela konteks 2M token dengan harga $2.00/$12.00 per 1 juta token, sedangkan GPT-5 Pro menyediakan konteks 400K token seharga $15.00/$120.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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Gemini 3 Pro
Model Unggulan Garis DepanGemini 3 Pro dari Google adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 2M, kecepatan 118 token/detik, indeks kecerdasan 62/100, serta tarif $
$2.00 / 1M
$12.00 / 1M
2M tokens
76.2%
GPT-5 Pro
Mesin Penalaran MendalamGPT-5 Pro dari OpenAI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 400K, kecepatan 55 token/detik, indeks kecerdasan 62/100, serta tarif $15/$120
$15.00 / 1M
$120.00 / 1M
400K tokens
78.5%
Perbedaan Utama Sekilas
- Gemini 3 Pro is 9.4x cheaper for API usage (input + output tokens combined).
- Gemini 3 Pro has a larger context window (2M vs 400K tokens).
- Gemini 3 Pro is faster at 118 tok/s vs 55 tok/s.
- GPT-5 Pro leads on SWE-bench coding (78.5% vs 76.2%).
| Feature | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 62 | 62 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $2.00 / 1M | $15.00 / 1M |
Output Price Cost per million output tokens | $12.00 / 1M | $120.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.74 / 1M | $16.05 / 1M |
Context Window Maximum input + output tokens | 2M tokens~3,000 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 66K | 272K |
Throughput Speed Tokens generated per second | 118 tok/s | 55 tok/s |
SWE-bench Verified Real-world software engineering | 76.2% | 78.5% |
GPQA Diamond Graduate-level reasoning | 73.5% | 87.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.20 / 1M | $1.50 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Gemini 3 Pro · Strengths & Key Advantages
- Jendela konteks 2M dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 76.2% · GPQA Diamond 73.5%)
- Kecepatan generasi tinggi 118 token/detik dengan latensi token pertama (TTFT) hanya 1800 ms
- Skema harga API kompetitif (tarif $2/$12 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
GPT-5 Pro · Strengths & Key Advantages
- Jendela konteks 400K dengan kapasitas output maksimum hingga 272K token (SWE-bench Verified 78.5% · GPQA Diamond 87.2%)
- Kecepatan generasi tinggi 55 token/detik dengan latensi token pertama (TTFT) hanya 4200 ms
- Skema harga API kompetitif (tarif $15/$120 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.40 | $20.40 |
Output Tokens / Task Tokens generated per task | 60K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 31K | 48K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Gemini 3 Pro | GPT-5 Pro |
|---|---|---|
| Official API Model ID (SDK) | models/gemini-3-pro | gpt-5-pro |
| API Protocol | Google Gemini API (generateContent) + OpenAI-Compatible SDK | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-11 | 2025-10 |
| Knowledge Cutoff | January 2025 | September 2024 |
| Architecture | Sparse Multimodal MoE | Maximum-compute unified reasoning model |
| 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) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($15/1M in) across full 400K window |
| Prompt Cache Policy & TTL | Implicit + Explicit Context Caching at $0.2/1M with configurable TTL | Automatic prefix caching at $1.5/1M (no extra cache-write fee) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Vertex AI Supervised Adapter Tuning & Context Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| 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) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published |
| 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 |
| Output Modalities | text | text |
Gemini 3 Pro vs GPT-5 Pro: Jawaban Cepat (FAQ)
Which model is faster?
Gemini 3 Pro is faster, generating 118 tokens per second compared with 55 tokens per second.
Which model is cheaper to run?
Gemini 3 Pro is cheaper at $1.74 per 1M tokens blended, compared with $16.05 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Gemini 3 Pro has lower latency, with a time to first token of 1.80s compared with 4.20s.
Which model has a larger context window?
Gemini 3 Pro has a larger context window, supporting 2M tokens compared with 400K tokens.
Kesimpulan
Baik Gemini 3 Pro (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-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 3 Pro unggul dalam penalaran dan pemrograman, Gemini 3 Pro memberikan kecepatan generasi token lebih tinggi, dan Gemini 3 Pro lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, Gemini 3 Pro atau GPT-5 Pro?+
Dalam indeks kecerdasan gabungan dan benchmark coding, Gemini 3 Pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API Gemini 3 Pro vs GPT-5 Pro?+
Gemini 3 Pro mengenakan biaya $2.00 / $12.00 per 1M token input/output, sedangkan GPT-5 Pro sebesar $15.00 / $120.00. Secara keseluruhan, Gemini 3 Pro lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
Gemini 3 Pro mendukung konteks 2M token dibandingkan 400K token pada GPT-5 Pro, sementara Gemini 3 Pro unggul dalam kecepatan output token per detik.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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- Gemini 3 Pro vs GPT-5.1: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.1 Chat vs Gemini 3 Pro: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5.1 Chat vs GPT-5 Pro: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-5 Pro vs Claude Opus 5: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
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.
Sumber resmi: Dokumentasi API resmi Google & OpenAI serta evaluasi benchmark independen (2026).