d'OpenAI historic phare modèle de fondation displaying human-level performances sur académique examinations, professionnel bar exams, et complexe programmation challenges.
Technical Specifications
- Provider
- OpenAI
- Category
- flagship
- Release Date
- 2023-03
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- $20 / month
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- 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-4
- 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 ($30/1M in) across full 8K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $7.5/1M (no extra cache-write fee)
- Computer Use & Browser GUI Agent
- 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
- 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-4 Cost, Context, Hardware & API Integration
For single-user chat, a $20/mo subscription caps your bill below this API volume.
Break-even point: ~5 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-4:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 21%
- GPQA Diamond
- 35.8%
- MMLU-Pro
- 68.2%
- HumanEval
- 67%
- Chatbot Arena Elo
- 1210pts
Strengths
- Passed uniform bar exam dans haut de gamme 10th percentile et élevé school Olympiads
- premier grand-échelle multimodal modèle de fondation demonstrating diagram interpretation
- supérieur complexe instruction following et policy conformité
Limitations & Trade-offs
- élevé API coût ($30/$60 par 1M tokens) par rapport à moderne optimized descendants
- Slow inférence vitesse (35 tok/s) et limité 8K default contexte
Editorial Assessment
le gold standard qui proved AI modèles could achieve human-expert capacités à travers standardized disciplines.
Best for: complexe multi-étapes juridique analyse, nuanced philosophical debate, et académique benchmark recherche
Compare GPT-4
Frequently Asked Questions about GPT-4
How much does the GPT-4 API cost per 1M tokens?+
GPT-4 by OpenAI is priced at $30 per 1M input tokens and $60 per 1M output tokens. With prompt caching enabled, cached input tokens cost $7.5 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the GPT-4 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-4's context window?+
GPT-4 features a 8K tokens context window, which equals approximately 6,144 English words or ~16 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 4,096 tokens.
Can I run GPT-4 locally on my own GPU (Open Weights)?+
No, GPT-4 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-4 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-4 perform on coding and reasoning benchmarks?+
GPT-4 achieves a composite Intelligence Index of 38/100, scoring 21% on SWE-bench Verified, 35.8% on GPQA Diamond, 68.2% on MMLU-Pro, and 1210 pts on Chatbot Arena Elo.
What is GPT-4 best used for?+
GPT-4 is best suited for: complexe multi-étapes juridique analyse, nuanced philosophical debate, et académique benchmark recherche. Assessment: le gold standard qui proved AI modèles could achieve human-expert capacités à travers standardized disciplines.
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-4:
L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.
Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).
Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.
La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.
Un standard ouvert créé par Anthropic permettant aux agents d'IA de se connecter de façon uniforme aux systèmes de fichiers locaux, aux environnements de développement et aux API tierces.
Une optimisation tarifaire et technique conservant les états d'attention des préfixes de prompts récurrents, réduisant les coûts d'entrée de 50 à 90 % tout en abaissant la latence.
Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.