GPT-5.3 Chat vs GPT-5.2 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5.3 Chat dari OpenAI dan GPT-5.2 Pro dari OpenAI adalah dua model AI unggulan. GPT-5.3 Chat menawarkan jendela konteks 128K token dengan harga $0.00/$0.00 per 1 juta token, sedangkan GPT-5.2 Pro menyediakan konteks 400K token seharga $17.50/$140.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
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GPT-5.3 Chat
Model Unggulan Garis DepanGPT-5.3 Chat dari OpenAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 128K, kecepatan 138 token/detik, indeks kecerdasan 69/100, serta akses
$0.00 / 1M
$0.00 / 1M
128K tokens
77%
GPT-5.2 Pro
Mesin Penalaran MendalamGPT-5.2 Pro dari OpenAI adalah model AI yang dirancang untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, menghadirkan jendela konteks 400K, kecepatan 50 token/detik, indeks kecerdasan 69/100, serta tarif $17.5/
$17.50 / 1M
$140.00 / 1M
400K tokens
79.4%
Perbedaan Utama Sekilas
- GPT-5.3 Chat is 1.0x cheaper for API usage (input + output tokens combined).
- GPT-5.2 Pro has a larger context window (400K vs 128K tokens).
- GPT-5.3 Chat is faster at 138 tok/s vs 50 tok/s.
- GPT-5.2 Pro leads on SWE-bench coding (79.4% vs 77.0%).
| Feature | GPT-5.3 Chat | GPT-5.2 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 69 | 69 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $0.00 / 1M | $17.50 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $140.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $18.73 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 16K | 128K |
Throughput Speed Tokens generated per second | 138 tok/s | 50 tok/s |
SWE-bench Verified Real-world software engineering | 77% | 79.4% |
GPQA Diamond Graduate-level reasoning | 78% | 79% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $1.75 / 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-5.3 Chat · Strengths & Key Advantages
- Jendela konteks 128K dengan kapasitas output maksimum hingga 16K token (SWE-bench Verified 77% · GPQA Diamond 78%)
- Kecepatan generasi tinggi 138 token/detik dengan latensi token pertama (TTFT) hanya 1060 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
GPT-5.2 Pro · Strengths & Key Advantages
- Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 79.4% · GPQA Diamond 79%)
- Kecepatan generasi tinggi 50 token/detik dengan latensi token pertama (TTFT) hanya 4400 ms
- Skema harga API kompetitif (tarif $17.5/$140 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-5.3 Chat | GPT-5.2 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.20 | $23.24 |
Output Tokens / Task Tokens generated per task | 56K | 70K |
Reasoning Tokens / Task Thinking tokens burned per task | 31K | 46K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5.3 Chat | GPT-5.2 Pro |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-3-chat | gpt-5-2-pro |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-03 | 2025-12 |
| Knowledge Cutoff | November 2025 | August 2025 |
| Architecture | Chat-tuned unified reasoning model | Maximum-compute unified reasoning model |
| 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 ($17.5/1M in) across full 400K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Automatic prefix caching at $1.75/1M (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-5.3 Chat vs GPT-5.2 Pro: Jawaban Cepat (FAQ)
Which model is faster?
GPT-5.3 Chat is faster, generating 138 tokens per second compared with 50 tokens per second.
Which model is cheaper to run?
GPT-5.3 Chat is cheaper at $0.00 per 1M tokens blended, compared with $18.73 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5.3 Chat has lower latency, with a time to first token of 1.06s compared with 4.40s.
Which model has a larger context window?
GPT-5.2 Pro has a larger context window, supporting 400K tokens compared with 128K tokens.
Kesimpulan
Baik GPT-5.3 Chat (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-5.2 Pro (Sangat cocok untuk penalaran logis mendalam, matematika tingkat lanjut, dan analisis ilmiah, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: GPT-5.3 Chat unggul dalam penalaran dan pemrograman, GPT-5.3 Chat memberikan kecepatan generasi token lebih tinggi, dan GPT-5.3 Chat lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-5.3 Chat atau GPT-5.2 Pro?+
Dalam indeks kecerdasan gabungan dan benchmark coding, GPT-5.3 Chat memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-5.3 Chat vs GPT-5.2 Pro?+
GPT-5.3 Chat mengenakan biaya $0.00 / $0.00 per 1M token input/output, sedangkan GPT-5.2 Pro sebesar $17.50 / $140.00. Secara keseluruhan, GPT-5.3 Chat lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-5.3 Chat mendukung konteks 128K token dibandingkan 400K token pada GPT-5.2 Pro, sementara GPT-5.3 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.
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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).