o1-pro vs o3-mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
o1-pro dari OpenAI dan o3-mini dari OpenAI adalah dua model AI unggulan. o1-pro menawarkan jendela konteks 200K token dengan harga $150.00/$600.00 per 1 juta token, sedangkan o3-mini menyediakan konteks 200K token seharga $1.10/$4.40 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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o1-pro
Mesin Penalaran Mendalamo1-pro dari OpenAI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 200K, kecepatan 22 token/detik, indeks kecerdasan 57/100, serta tarif $150/$600 p
$150.00 / 1M
$600.00 / 1M
200K tokens
51.5%
o3-mini
Mesin Penalaran Mendalamo3-mini dari OpenAI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 200K, kecepatan 85 token/detik, indeks kecerdasan 51/100, serta tarif $1.1/$4.4
$1.10 / 1M
$4.40 / 1M
200K tokens
49%
Perbedaan Utama Sekilas
- o3-mini is 127.6x cheaper for API usage (input + output tokens combined).
- o3-mini is faster at 85 tok/s vs 22 tok/s.
- o1-pro leads on SWE-bench coding (51.5% vs 49.0%).
| Feature | o1-pro | o3-mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 57 | 51 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $150.00 / 1M | $1.10 / 1M |
Output Price Cost per million output tokens | $600.00 / 1M | $4.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $116.25 / 1M | $1.05 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 100K | 100K |
Throughput Speed Tokens generated per second | 22 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 51.5% | 49% |
GPQA Diamond Graduate-level reasoning | 79% | 79.7% |
Cached Input Price Prompt caching discount per 1M tokens | $37.50 / 1M | $0.55 / 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.
o1-pro · Strengths & Key Advantages
- Jendela konteks 200K dengan kapasitas output maksimum hingga 100K token (SWE-bench Verified 51.5% · GPQA Diamond 79%)
- Kecepatan generasi tinggi 22 token/detik dengan latensi token pertama (TTFT) hanya 4200 ms
- Skema harga API kompetitif (tarif $150/$600 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
o3-mini · Strengths & Key Advantages
- Jendela konteks 200K dengan kapasitas output maksimum hingga 100K token (SWE-bench Verified 49% · GPQA Diamond 79.7%)
- Kecepatan generasi tinggi 85 token/detik dengan latensi token pertama (TTFT) hanya 1400 ms
- Skema harga API kompetitif (tarif $1.1/$4.4 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
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | o1-pro | o3-mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $94.20 | $1.30 |
Output Tokens / Task Tokens generated per task | 62K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 45K | 25K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | o1-pro | o3-mini |
|---|---|---|
| Official API Model ID (SDK) | o1-pro | o3-mini |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-03 | 2025-01 |
| Knowledge Cutoff | October 2023 | October 2023 |
| Architecture | High-compute reasoning transformer | Chain-of-Thought Reasoning Dense |
| 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) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($150/1M in) across full 200K window | Flat rate ($1.1/1M in) across full 200K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $37.5/1M (no extra cache-write fee) | Automatic prefix caching at $0.55/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | 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) | Text BPE (~4 chars/token) |
| 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 | 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 | text |
| Output Modalities | text | text |
o1-pro vs o3-mini: Jawaban Cepat (FAQ)
Which is more intelligent, o1-pro or o3-mini?
o1-pro is more intelligent. It scores 57 compared with 51 on the composite Intelligence Index.
Which model is faster?
o3-mini is faster, generating 85 tokens per second compared with 22 tokens per second.
Which model is cheaper to run?
o3-mini is cheaper at $1.05 per 1M tokens blended, compared with $116.25 (7:2:1 cache:input:output ratio).
Which model has lower latency?
o3-mini has lower latency, with a time to first token of 1.40s compared with 4.20s.
Kesimpulan
Baik o1-pro (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun o3-mini (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: o1-pro unggul dalam penalaran dan pemrograman, o3-mini memberikan kecepatan generasi token lebih tinggi, dan o3-mini lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, o1-pro atau o3-mini?+
Dalam indeks kecerdasan gabungan dan benchmark coding, o1-pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API o1-pro vs o3-mini?+
o1-pro mengenakan biaya $150.00 / $600.00 per 1M token input/output, sedangkan o3-mini sebesar $1.10 / $4.40. Secara keseluruhan, o3-mini lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
o1-pro mendukung konteks 200K token dibandingkan 200K token pada o3-mini, sementara o3-mini 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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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 OpenAI & OpenAI serta evaluasi benchmark independen (2026).