Key Takeaways
- GPT-5.4 is the new default: Launched March 5, 2026, it merges GPT-5.3 Codex's coding prowess with broader reasoning, a 1M-token context, and native computer use.
- Six models serve different needs: Flagship (5.4), balanced (5.4 Mini), fast (5.4 Nano), coding specialist (5.3 Codex), everyday (5.3 Instant), and legacy (5.2 Thinking).
- Price spans 10x: From $0.30/MTok (GPT-5.3 Instant) to $2.50/MTok (GPT-5.4) on input — choosing the right model directly impacts your bill.
- GPT-5.2 retires June 5: Migrate now to avoid disruption.
The Complete Guide to OpenAI's GPT-5 Model Family
OpenAI's GPT-5 family has grown into six distinct models, each optimized for a different trade-off between capability, speed, and cost. Choosing the wrong model means either overpaying for simple tasks or under-powering complex ones.
This guide covers every model, with pricing, benchmarks, and a clear decision framework.
The Full Lineup (March 2026)
| Model | Role | Input Cost | Output Cost | Context | Released |
|---|---|---|---|---|---|
| GPT-5.4 | Flagship reasoning + coding | $2.50/MTok | $10.00/MTok | 1.05M | Mar 5, 2026 |
| GPT-5.4 Mini | Fast balanced | Lower | Lower | Smaller | Mar 2026 |
| GPT-5.4 Nano | Lowest latency | Lowest | Lowest | Smallest | Mar 2026 |
| GPT-5.3 Codex | Coding specialist | $1.75/MTok | $7.00/MTok | 400K | Mar 3, 2026 |
| GPT-5.3 Instant | Everyday tasks | ~$0.30/MTok | ~$1.20/MTok | Standard | Mar 3, 2026 |
| GPT-5.2 Thinking | Legacy flagship | Higher | Higher | Smaller | Previous |
Sources: OpenAI API Models, FelloAI Comparison
GPT-5.4: The New Flagship
GPT-5.4 is OpenAI's most capable model — the first to merge frontier reasoning with frontier coding in a single architecture.
What Makes It Special
- 1,050,000-token context window — Process entire large codebases, complete documentation sets, and long conversation histories without chunking
- Native computer use — Interact with desktop applications, browsers, and system tools programmatically
- 57.7% on SWE-Bench Pro — State-of-the-art coding benchmark performance
- 83% on GDPval knowledge tasks — Matches or exceeds industry professionals
- Token efficient — Fewer output tokens per task despite higher nominal pricing
When to Use GPT-5.4
- Complex coding tasks requiring deep reasoning
- Multi-step autonomous workflows (via Codex CLI)
- Long-context analysis (>400K tokens)
- Tasks requiring computer use capabilities
- Any new project where you need the best model available
Pricing
| Tier | Input | Output | Cached Input |
|---|---|---|---|
| Standard | $2.50/MTok | $10.00/MTok | $0.63/MTok |
GPT-5.4 Mini: The Balanced Choice
GPT-5.4 Mini inherits GPT-5.4's architecture at a lower cost and latency point. It's designed for applications that need good reasoning without paying flagship prices.
When to Use GPT-5.4 Mini
- Production APIs where cost per request matters
- Applications needing a balance of speed and quality
- Chatbot backends with moderate complexity
- Workflows where GPT-5.4 is overkill but GPT-5.3 Instant isn't enough
GPT-5.4 Nano: The Speed Demon
GPT-5.4 Nano is optimized for the lowest possible latency. It trades reasoning depth for raw speed.
When to Use GPT-5.4 Nano
- Real-time autocomplete and suggestions
- Latency-critical production endpoints
- High-volume, low-complexity classification tasks
- Mobile applications where response time is critical
GPT-5.3 Codex: The Coding Specialist
GPT-5.3 Codex remains the best model for cost-sensitive, input-heavy coding workflows. It runs 25% faster than GPT-5.2 Codex and costs less per input token than GPT-5.4.
When to Use GPT-5.3 Codex
- Terminal-heavy batch coding operations
- Workflows that repeatedly send large repository context
- Cost-optimized agentic coding pipelines
- Tasks where the 400K context window is sufficient
When to Upgrade to GPT-5.4
- You need >400K tokens of context
- You need computer use capabilities
- You need knowledge work beyond coding
- The 43% input cost premium is worth the broader capabilities
Pricing
| Tier | Input | Output | Cached Input |
|---|---|---|---|
| Standard | $1.75/MTok | $7.00/MTok | $0.44/MTok |
GPT-5.3 Instant: The Everyday Workhorse
GPT-5.3 Instant is the cheapest GPT-5 model and the best choice for high-volume, everyday tasks.
Key Strengths
- 26.8% fewer hallucinations than predecessor models
- Excellent at: Q&A, how-tos, technical writing, translation
- Lowest cost: ~$0.30/$1.20 per million tokens
- High throughput: Optimized for speed
When to Use GPT-5.3 Instant
- Customer support chatbots
- Content generation at scale
- Translation and localization
- Simple Q&A systems
- Any high-volume application where cost per request matters most
Pricing
| Tier | Input | Output |
|---|---|---|
| Standard | ~$0.30/MTok | ~$1.20/MTok |
GPT-5.2 Thinking: Legacy (Retiring June 2026)
GPT-5.2 was the previous flagship model. It introduced a three-tier architecture (Instant, Thinking, and Pro) but has been superseded by GPT-5.4 across all benchmarks.
Migration Timeline
- Now → June 5, 2026: GPT-5.2 Thinking available under Legacy Models
- June 5, 2026: GPT-5.2 Thinking retired. API calls will fail.
- Action Required: Update
modelparameter fromgpt-5.2-thinkingtogpt-5.4
# Before (will stop working June 5, 2026)
model="gpt-5.2-thinking"
# After
model="gpt-5.4"
Decision Framework: Which Model to Use
By Use Case
| Use Case | Recommended Model | Why |
|---|---|---|
| Complex coding + reasoning | GPT-5.4 | Best capability, 1M context |
| Daily coding (cost-sensitive) | GPT-5.3 Codex | Lower input cost, strong coding |
| General chatbot/Q&A | GPT-5.3 Instant | Cheapest, fast, low hallucination |
| Production API (balanced) | GPT-5.4 Mini | Good quality, reasonable cost |
| Real-time autocomplete | GPT-5.4 Nano | Lowest latency |
| Science/research | GPT-5.4 | Deepest reasoning |
By Budget
| Monthly Budget | Strategy |
|---|---|
| <$50 | GPT-5.3 Instant for everything |
| $50-200 | GPT-5.3 Instant + GPT-5.3 Codex for coding |
| $200-1,000 | GPT-5.4 as default, GPT-5.3 Instant for simple tasks |
| $1,000+ | GPT-5.4 for everything, or hybrid routing |
The Router Pattern
The most cost-effective approach for production applications:
Request → Classify Complexity
├── Simple (60%) → GPT-5.3 Instant ($0.30/MTok)
├── Medium (25%) → GPT-5.4 Mini
├── Complex (10%) → GPT-5.4 ($2.50/MTok)
└── Coding (5%) → GPT-5.3 Codex ($1.75/MTok)
This pattern can reduce costs by 70-80% compared to running GPT-5.4 for all requests, with minimal quality impact.
GPT-5 vs the Competition
How does the GPT-5 family stack up against Claude and Gemini?
| Model | Input Cost | SWE-Bench | Context | Strength |
|---|---|---|---|---|
| GPT-5.4 | $2.50/MTok | 57.7% (Pro) | 1.05M | Broadest capability |
| Claude Opus 4.6 | $15/MTok | 80.8% (Verified) | 1M | Deepest reasoning |
| Claude Sonnet 4.6 | $3/MTok | 79.6% (Verified) | 1M | Best value reasoning |
| Gemini 3.1 Pro | Varies | Competitive | 2M | Largest context |
Each model family has strengths. GPT-5.4 offers the most balanced capability set; Claude leads on coding benchmarks; Gemini leads on context window size.
Beyond the API: Building Without Code
All GPT-5 models are tools for developers. Whether you use GPT-5.4 directly or through Codex CLI, you still need programming knowledge to build applications.
If you want to build an app without writing code, platforms like ZBuild let you describe your application in plain language and get a complete working product — powered by AI models like these behind the scenes.
Summary
OpenAI's GPT-5 family offers a model for every use case and budget:
| Model | One-Liner |
|---|---|
| GPT-5.4 | Best overall, use this if unsure |
| GPT-5.4 Mini | Good balance of speed and cost |
| GPT-5.4 Nano | Fastest, for latency-critical apps |
| GPT-5.3 Codex | Cheapest per-token for heavy coding |
| GPT-5.3 Instant | Cheapest overall, for everyday tasks |
| GPT-5.2 | Retiring June 5 — migrate now |
The right choice depends on your workload, budget, and latency requirements. When in doubt, start with GPT-5.4 and optimize down to cheaper models as you understand your traffic patterns.
Published by the ZBuild Team. Build apps without coding at zbuild.io.
Sources
- OpenAI: Introducing GPT-5.4
- OpenAI: Introducing GPT-5.2
- OpenAI API Models
- OpenAI: Using GPT-5.4
- OpenAI Help Center: GPT-5.3 and GPT-5.4
- OpenAI Codex Models
- FelloAI: Ultimate ChatGPT Model Comparison
- Zapier: OpenAI Models Guide
- Nathan Lambert: GPT-5.4 Analysis