el monumental 175-miles de millones parámetro modelo fundacional que revealed few-shot aprendizaje en contexto y ushered en el moderno LLM comercial era.
Technical Specifications
- Provider
- OpenAI
- Category
- historical
- Release Date
- 2020-06
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- $20 / month
- Reasoning Effort Control
- Fixed
- Structured Outputs
- No
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- gpt-3
- Supported SDK & API Protocol
- OpenAI Responses API & Chat Completions v1
- Lifecycle & Deprecation Status
- Legacy Stable (Upgrade path available in OpenAI lineup)
- Production Rate Limits (RPM & TPM)
- 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($20/1M in) across full 2K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $5/1M (no extra cache-write fee)
- Computer Use & Browser GUI Agent
- Text-only completion (No GUI action loop)
- MCP & Parallel Tool Calling
- Prompt-based JSON extraction only
- Web Search Grounding & Code Sandbox
- Native Web Search tool + Hosted Code Interpreter & File Search RAG
- Fine-Tuning & Distillation Support
- Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed OpenAI Cloud API
- System Card & Safety Framework
- OpenAI Preparedness Framework Audited & System Card Published
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
GPT-3 Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~10 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to GPT-3:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 43.9%
- HumanEval
- 28.2%
- Chatbot Arena Elo
- 980pts
Strengths
- Groundbreaking few-shot aprendizaje en contexto ability sin actualizaciones de gradiente
- Broad conocimiento general spanning historia humana, literatura científica, y basic code
- Impulsó el ecosistema global de API de IA generativa
Limitations & Trade-offs
- ventana de contexto limitado un 2,048 tokens
- alto inferencia costo ($20/1M tokens) antes de moderno optimización passes
- Lacked RLHF alignment en original base form
Editorial Assessment
el breakthrough modelo que proved escala conduce un saltos cualitativos en inteligencia artificial general capacidades.
Best for: aprendizaje en contexto pruebas de rendimiento, historic evaluación, y legacy generación cargas de trabajo
Compare GPT-3
Frequently Asked Questions about GPT-3
How much does the GPT-3 API cost per 1M tokens?+
GPT-3 by OpenAI is priced at $20 per 1M input tokens and $20 per 1M output tokens. With prompt caching enabled, cached input tokens cost $5 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the GPT-3 pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in GPT-3's context window?+
GPT-3 features a 2K tokens context window, which equals approximately 1,536 English words or ~4 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 2,048 tokens.
Can I run GPT-3 locally on my own GPU (Open Weights)?+
No, GPT-3 is a proprietary closed-weights model hosted by OpenAI. It cannot be downloaded for local GPU execution and must be accessed via OpenAI's official API or cloud platform.
Does OpenAI train on data sent to the GPT-3 API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (OpenAI Terms). Full commercial ownership of generated outputs. Supported deployment channels include: OpenAI Platform API, Microsoft Azure OpenAI Foundry.
How does GPT-3 perform on coding and reasoning benchmarks?+
GPT-3 achieves a composite Intelligence Index of 22/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 43.9% on MMLU-Pro, and 980 pts on Chatbot Arena Elo.
What is GPT-3 best used for?+
GPT-3 is best suited for: aprendizaje en contexto pruebas de rendimiento, historic evaluación, y legacy generación cargas de trabajo. Assessment: el breakthrough modelo que proved escala conduce un saltos cualitativos en inteligencia artificial general capacidades.
OpenAI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to OpenAI's flagship reasoning tier:
GPT-6 Astra
GPT-6.1 Sol
GPT-6 Sol
GPT-6 Luna
GPT-5.6 Sol
GPT-5.6 Terra
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to GPT-3:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
Una optimización donde los proveedores almacenan estados de atención previos para prefijos de prompts frecuentes, reduciendo el coste de entrada hasta en un 90% y acelerando la respuesta.
Una optimización de memoria GPU que almacena matrices de atención previas (Key y Value) para evitar recalcular tokens ya procesados, acelerando la generación de respuestas en streaming.
La arquitectura de red neuronal introducida en 2017 que impulsa los LLM modernos, empleando mecanismos de autoatención para procesar secuencias completas en paralelo.
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: OpenAI paper: Language Models are Few-Shot Learners (2020)↗