| Signal | GPT-5.4 Mini | Delta | GPT-5.4 Pro |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 90 | -- | |
Pricing | 96 | +91 | |
Context window size | 89 | -7 | |
Recency | 100 | -- | |
Output Capacity | 85 | -- | |
| Overall Result | 1 wins | of 6 | 1 wins |
Score History
79.3
current score
GPT-5.4 Pro
right now
91.9
current score
OpenAI
OpenAI
GPT-5.4 Mini saves you $11700.00/month
That's $140400.00/year compared to GPT-5.4 Pro at your current usage level of 100K calls/month.
| Metric | GPT-5.4 Mini | GPT-5.4 Pro | Winner |
|---|---|---|---|
| Overall Score | 79 | 92 | GPT-5.4 Pro |
| Rank | #43 | #1 | GPT-5.4 Pro |
| Quality Rank | #43 | #1 | GPT-5.4 Pro |
| Adoption Rank | #43 | #1 | GPT-5.4 Pro |
| Parameters | -- | -- | -- |
| Context Window | 400K | 1050K | GPT-5.4 Pro |
| Pricing | $0.75/$4.50/M | $30.00/$180.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5.4 Mini |
| Benchmarks | 90 | 90 | GPT-5.4 Mini |
| Pricing | 96 | 5 | GPT-5.4 Mini |
| Context window size | 89 | 96 | GPT-5.4 Pro |
| Recency | 100 | 100 | GPT-5.4 Mini |
| Output Capacity | 85 | 85 | GPT-5.4 Mini |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 79/100 (rank #43), placing it in the top 86% of all 290 models tracked.
Scores 92/100 (rank #1), placing it in the top 100% of all 290 models tracked.
GPT-5.4 Pro has a 13-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GPT-5.4 Mini offers 98% better value per quality point. At 1M tokens/day, you'd spend $78.75/month with GPT-5.4 Mini vs $3150.00/month with GPT-5.4 Pro - a $3071.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GPT-5.4 Mini also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($4.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (92/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5.4 Pro clearly outperforms GPT-5.4 Mini with a significant 12.600000000000009-point lead. For most general use cases, GPT-5.4 Pro is the stronger choice. However, GPT-5.4 Mini may still excel in niche scenarios.
Best for Quality
GPT-5.4 Mini
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.4 Mini
98% lower pricing; better value at scale
Best for Reliability
GPT-5.4 Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.4 Mini
Stronger community support and better developer experience
Best for Production
GPT-5.4 Mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.4 Mini | GPT-5.4 Pro |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
OpenAI
GPT-5.4 Mini saves you $263.25/month
That's 98% cheaper than GPT-5.4 Pro at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.4 Mini | GPT-5.4 Pro |
|---|---|---|
| Context Window | 400K | 1.1M |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Mar 17, 2026 | Mar 5, 2026 |
The identical scores suggest both models achieve similar performance on coding benchmarks, making the $180/M output pricing for Pro difficult to justify purely on quality metrics. The main differentiator is Pro's 1.1M token context window versus Mini's 400K, which only matters for extremely large codebases or multi-file analysis tasks that exceed 400K tokens.
At 8M output tokens daily, GPT-5.4 Mini costs $36/day ($4.5/M output) while Pro costs $1,440/day ($180/M output), a staggering $42,000 monthly difference. Unless your use case absolutely requires analyzing code repositories larger than 400K tokens in a single context, Mini delivers identical capabilities and performance at 2.5% of Pro's cost.
Pro's 1.1M context advantage only becomes relevant for analyzing entire monorepos or processing multiple large files simultaneously that exceed 400K tokens. For typical coding tasks like single-file analysis, PR reviews, or even multi-file refactoring under 100K tokens, Mini's 400K window provides 4x headroom while saving $175.50 per million output tokens.
While output tokens are 40x more expensive on Pro ($180/M vs $4.5/M), input tokens are also 40x pricier ($30/M vs $0.75/M), maintaining a consistent 6:1 output-to-input ratio for both models. This uniform scaling suggests OpenAI prices purely on context window size rather than actual performance differences, making Mini the obvious choice for any workload that fits within 400K tokens.
The only technical justification for Pro's 40x premium is processing inputs between 400K-1.1M tokens, such as analyzing entire documentation sets with images, multiple large codebases, or extensive conversation histories. Since both share the same 128K output limit and support vision, function calling, and web search equally, Pro is essentially a luxury tax on context length that few coding workflows actually require.