GPT-3 vs GPT-3.5 Turbo
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-3 dari OpenAI dan GPT-3.5 Turbo dari OpenAI adalah dua model AI unggulan. GPT-3 menawarkan jendela konteks 2K token dengan harga $20.00/$20.00 per 1 juta token, sedangkan GPT-3.5 Turbo menyediakan konteks 16.4K token seharga $0.50/$1.50 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
Ganti & Bandingkan Model Apa Saja
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
GPT-3
Model Generasi KlasikGPT-3 dari OpenAI adalah model AI yang dirancang untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, menghadirkan jendela konteks 2K, kecepatan 40 token/detik, indeks kecerdasan 22/100, serta tarif $20/$20 per 1M tok
$20.00 / 1M
$20.00 / 1M
2K tokens
N/A
GPT-3.5 Turbo
Inferensi Super CepatGPT-3.5 Turbo dari OpenAI adalah model AI yang dirancang untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, menghadirkan jendela konteks 16K, kecepatan 90 token/detik, indeks kecerdasan 30/100, serta tarif
$0.50 / 1M
$1.50 / 1M
16.4K tokens
12.5%
Perbedaan Utama Sekilas
- GPT-3.5 Turbo is 22.4x cheaper for API usage (input + output tokens combined).
- GPT-3.5 Turbo has a larger context window (16K vs 2K tokens).
- GPT-3.5 Turbo is faster at 90 tok/s vs 40 tok/s.
| Feature | GPT-3 | GPT-3.5 Turbo |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 22 | 30 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $20.00 / 1M | $0.50 / 1M |
Output Price Cost per million output tokens | $20.00 / 1M | $1.50 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $9.50 / 1M | $0.42 / 1M |
Context Window Maximum input + output tokens | 2K tokens~3 A4 pages of text | 16.4K tokens~25 A4 pages of text |
Max Output Tokens Per single request | 2K | 4K |
Throughput Speed Tokens generated per second | 40 tok/s | 90 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 12.5% |
GPQA Diamond Graduate-level reasoning | N/A | 28% |
Cached Input Price Prompt caching discount per 1M tokens | $5.00 / 1M | $0.25 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor 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.
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-3 · Strengths & Key Advantages
- Jendela konteks 2K dengan kapasitas output maksimum hingga 2K token (MMLU-Pro 43.9% · Arena Elo 980)
- Kecepatan generasi tinggi 40 token/detik dengan latensi token pertama (TTFT) hanya 900 ms
- Skema harga API kompetitif (tarif $20/$20 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-3.5 Turbo · Strengths & Key Advantages
- Jendela konteks 16K dengan kapasitas output maksimum hingga 4K token (SWE-bench Verified 12.5% · GPQA Diamond 28%)
- Kecepatan generasi tinggi 90 token/detik dengan latensi token pertama (TTFT) hanya 450 ms
- Skema harga API kompetitif (tarif $0.5/$1.5 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-3 | GPT-3.5 Turbo |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $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-3 | GPT-3.5 Turbo |
|---|---|---|
| Official API Model ID (SDK) | gpt-3 | gpt-3-5-turbo |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2020-06 | 2022-11 |
| Knowledge Cutoff | June 2020 | September 2021 |
| Architecture | Autoregressive Transformer (Davinci) | Transformer with RLHF & PPO |
| Parameters | 175B | Confidential (est. 20B MoE / 175B base) |
| 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 ($20/1M in) across full 2K window | Flat rate ($0.5/1M in) across full 16K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $5/1M (no extra cache-write fee) | Automatic prefix caching at $0.25/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Text-only completion (No GUI action loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Prompt-based JSON extraction only | 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) | 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 | text |
| Output Modalities | text | text |
GPT-3 vs GPT-3.5 Turbo: Jawaban Cepat (FAQ)
Which is more intelligent, GPT-3 or GPT-3.5 Turbo?
GPT-3.5 Turbo is more intelligent. It scores 30 compared with 22 on the composite Intelligence Index.
Which model is faster?
GPT-3.5 Turbo is faster, generating 90 tokens per second compared with 40 tokens per second.
Which model is cheaper to run?
GPT-3.5 Turbo is cheaper at $0.42 per 1M tokens blended, compared with $9.50 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-3.5 Turbo has lower latency, with a time to first token of 0.45s compared with 0.90s.
Which model has a larger context window?
GPT-3.5 Turbo has a larger context window, supporting 16.4K tokens compared with 2K tokens.
Kesimpulan
Baik GPT-3 (Sangat cocok untuk asisten percakapan, peringkasan dokumen, dan beban kerja bisnis umum, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-3.5 Turbo (Sangat cocok untuk interaksi real-time dengan latensi sangat rendah dan routing bervolume tinggi, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: GPT-3.5 Turbo unggul dalam penalaran dan pemrograman, GPT-3.5 Turbo memberikan kecepatan generasi token lebih tinggi, dan GPT-3.5 Turbo lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-3 atau GPT-3.5 Turbo?+
Dalam indeks kecerdasan gabungan dan benchmark coding, GPT-3.5 Turbo memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-3 vs GPT-3.5 Turbo?+
GPT-3 mengenakan biaya $20.00 / $20.00 per 1M token input/output, sedangkan GPT-3.5 Turbo sebesar $0.50 / $1.50. Secara keseluruhan, GPT-3.5 Turbo lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-3 mendukung konteks 2K token dibandingkan 16.4K token pada GPT-3.5 Turbo, sementara GPT-3.5 Turbo 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
- GPT-4 vs GPT-3.5 Turbo: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- GPT-4 vs GPT-3: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Aion-3.0 vs Aion-Mini: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Aion-3.0 vs Gemini 3.6 Flash: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Aion-Mini vs Laguna XS 2.1: Perbandingan Benchmark, Harga API & Kecepatan (2026)Bandingkan
- Aya Expanse 32B vs Llama 3.2 90B Vision: 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 OpenAI & OpenAI serta evaluasi benchmark independen (2026).