GPT-5 Chat vs o3-pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5 Chat dari OpenAI dan o3-pro dari OpenAI adalah dua model AI unggulan. GPT-5 Chat menawarkan jendela konteks 128K token dengan harga $0.00/$0.00 per 1 juta token, sedangkan o3-pro menyediakan konteks 200K token seharga $20.00/$80.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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GPT-5 Chat
Model Unggulan Garis DepanGPT-5 Chat dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 128K, kecepatan 140 token/detik, indeks kecerdasan 56/100, serta akses g
$0.00 / 1M
$0.00 / 1M
128K tokens
70%
o3-pro
Mesin Penalaran Mendalamo3-pro dari OpenAI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 200K, kecepatan 30 token/detik, indeks kecerdasan 58/100, serta tarif $20/$80 per
$20.00 / 1M
$80.00 / 1M
200K tokens
71.5%
Perbedaan Utama Sekilas
- GPT-5 Chat is 1.0x cheaper for API usage (input + output tokens combined).
- o3-pro has a larger context window (200K vs 128K tokens).
- GPT-5 Chat is faster at 140 tok/s vs 30 tok/s.
- o3-pro leads on SWE-bench coding (71.5% vs 70.0%).
| Feature | GPT-5 Chat | o3-pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 56 | 58 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $0.00 / 1M | $20.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $80.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $15.50 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 16K | 100K |
Throughput Speed Tokens generated per second | 140 tok/s | 30 tok/s |
SWE-bench Verified Real-world software engineering | 70% | 71.5% |
GPQA Diamond Graduate-level reasoning | 79% | 79.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $5.00 / 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.
GPT-5 Chat · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 70% · GPQA Diamond 79%)
- Kecepatan generasi tinggi 140 token/detik dengan latensi token pertama (TTFT) hanya 1050 ms
- Skema harga API kompetitif (akses gratis open-weights) 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
o3-pro · Strengths & Key Advantages
- Jendela konteks 200K dengan kapasitas output maksimum hingga 100K token (SWE-bench Verified 71.5% · GPQA Diamond 79.5%)
- Kecepatan generasi tinggi 30 token/detik dengan latensi token pertama (TTFT) hanya 5200 ms
- Skema harga API kompetitif (tarif $20/$80 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 | GPT-5 Chat | o3-pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.50 | $11.68 |
Output Tokens / Task Tokens generated per task | 54K | 58K |
Reasoning Tokens / Task Thinking tokens burned per task | 28K | 38K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5 Chat | o3-pro |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-chat | o3-pro |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-08 | 2025-06 |
| Knowledge Cutoff | September 2024 | June 2024 |
| Architecture | Chat-tuned unified reasoning model | High-effort reasoning transformer |
| 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) | Free across full context window (only KV-cache VRAM scales) | Flat rate ($20/1M in) across full 200K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Automatic prefix caching at $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 | 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) · 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 | 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, vision |
| Output Modalities | text | text |
GPT-5 Chat vs o3-pro: Jawaban Cepat (FAQ)
Which is more intelligent, GPT-5 Chat or o3-pro?
o3-pro is more intelligent. It scores 58 compared with 56 on the composite Intelligence Index.
Which model is faster?
GPT-5 Chat is faster, generating 140 tokens per second compared with 30 tokens per second.
Which model is cheaper to run?
GPT-5 Chat is cheaper at $0.00 per 1M tokens blended, compared with $15.50 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5 Chat has lower latency, with a time to first token of 1.05s compared with 5.20s.
Which model has a larger context window?
o3-pro has a larger context window, supporting 200K tokens compared with 128K tokens.
Kesimpulan
Baik GPT-5 Chat (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun o3-pro (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: o3-pro unggul dalam penalaran dan pemrograman, GPT-5 Chat memberikan kecepatan generasi token lebih tinggi, dan GPT-5 Chat lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-5 Chat atau o3-pro?+
Dalam indeks kecerdasan gabungan dan benchmark coding, o3-pro memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-5 Chat vs o3-pro?+
GPT-5 Chat mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan o3-pro sebesar $20.00 / $80.00. Secara keseluruhan, GPT-5 Chat lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-5 Chat mendukung konteks 128K token dibandingkan 200K token pada o3-pro, sementara GPT-5 Chat 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).