d'OpenAI compact, coût-efficient petit modèle designed à replace GPT-3.5 Turbo à travers élevé-volume classification, extraction, et utility tâches.
Technical Specifications
- Provider
- OpenAI
- Category
- lightweight
- Release Date
- 2024-07
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- 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-4o-mini
- 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 ($0.15/1M in) across full 128K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $0.075/1M (no extra cache-write fee)
- Computer Use & Browser GUI Agent
- Supported (Screen coordinate grounding, browser & desktop GUI action loops)
- 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) · Vision (~258–765 tokens per image tile)
- 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-4o mini Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $4.25/mo vs $20 flat plan).
Break-even point: ~635 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-4o mini:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 24.5%
- GPQA Diamond
- 40.2%
- MMLU-Pro
- 58.5%
- HumanEval
- 82%
- Humanity's Last Exam
- 6.4%
- Terminal-Bench
- 16.2%
- SciCode
- 14.7%
- LiveCodeBench
- 28.3%
- AIME
- 46.2%
- Long-Context Reasoning
- 52.7%
- Chatbot Arena Elo
- 1228pts
Strengths
- Economical tarification ($0.15 dans / $0.60 out par 1M tokens)
- complet vision multimodal support à faible coût
- élevé sortie token limit (16K tokens)
- Consistent function calling et JSON sortie reliability
Limitations & Trade-offs
- limité raisonnement pour complexe logiciel architecture
- Slightly supérieur tarification que Gemini 2.0 Flash ($0.15 vs $0.10)
Editorial Assessment
un fiable et proven utility modèle pour production pipelines requiring standard intelligence avec minimal latence.
Best for: données extraction, client support routage, et léger web scraping
Compare GPT-4o mini
Frequently Asked Questions about GPT-4o mini
How much does the GPT-4o mini API cost per 1M tokens?+
GPT-4o mini by OpenAI is priced at $0.15 per 1M input tokens and $0.6 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.075 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the GPT-4o mini 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-4o mini's context window?+
GPT-4o mini features a 128K tokens context window, which equals approximately 96,000 English words or ~256 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 16,384 tokens.
Can I run GPT-4o mini locally on my own GPU (Open Weights)?+
No, GPT-4o mini 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-4o mini 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-4o mini perform on coding and reasoning benchmarks?+
GPT-4o mini achieves a composite Intelligence Index of 30/100, scoring 24.5% on SWE-bench Verified, 40.2% on GPQA Diamond, 58.5% on MMLU-Pro, and 1228 pts on Chatbot Arena Elo.
What is GPT-4o mini best used for?+
GPT-4o mini is best suited for: données extraction, client support routage, et léger web scraping. Assessment: un fiable et proven utility modèle pour production pipelines requiring standard intelligence avec minimal latence.
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-4o mini:
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.