New Model Alert: Drainpipe Now Supports OpenAI GPT 5, GPT 5 Mini, GPT 5 Nano
Drainpipe Supports GPT 5
Drainpipe is pleased to announce support for the new OpenAI GPT 5 models:
- OpenAI GPT-5
- OpenAI GPT-5 Mini
- OpenAI GPT-5 Nano
All three of these models are immediately available to all Drainpipe Platform users.
What’s New in GPT 5?
GPT‑5 sets a new bar, combining advanced reasoning, flexibility, safety, and usability across both consumer and professional contexts.
- Smarter, Faster, More Useful
- GPT-5 delivers more accurate responses faster with reduced hallucinations and greater reliability.
- Multiple Versions for Different Needs
- GPT‑5‑main and GPT‑5‑main‑mini for fast, general inference.
- GPT‑5‑thinking, thinking‑mini, and thinking‑nano for deeper reasoning tasks.
- GPT‑5-mini and GPT‑5‑nano, optimized for cost and speed at very low prices.
- Unified Auto‑Routing System
- Instead of forcing users to select a specific model, GPT‑5 uses a “real‑time router” that automatically selects the appropriate variants based on the prompt’s complexity, requirements, and usage limits.
- Safer, More Responsible Output
- Designed to better handle limitations and admit when it doesn’t know something.
Benchmarks: GPT-4 vs GPT-5
| Benchmark / Task | What It Measures | GPT‑4 / GPT‑4o | GPT‑5 | Improvement |
|---|---|---|---|---|
| AIME 2025 (Math) | High-school level competition math problems (AMC 10/12, AIME); tests symbolic and numerical reasoning skills. | 14% (1) | 94.6% (2) | Major boost in symbolic math and number reasoning capabilities. |
| GPQA (Graduate-Level Reasoning) | Graduate-level (PhD) scientific multiple-choice questions across physics, chemistry, biology, etc. | 70.1% (2) | 85.7% (2) | Stronger long-context and abstract reasoning performance. |
| SWE-bench Verified | Real-world software engineering: fixing actual bugs in open-source GitHub repos using test cases as validation. | 30.8% (2) | 74.9% (2) | More than 2× improvement; major gains in code understanding, reasoning, and debugging. |
| Aider Polyglot | Solving programming tasks across many programming languages, including rare or non-English languages. | 43.3% (3) | 88% (2) | Sets new benchmark for multilingual coding ability. |
| MMMU (Multimodal Multitask Understanding) | Graduate-level multimodal tasks (e.g., interpreting charts, diagrams, and written content) across diverse subjects. | 72.2% (2) | 84.2% (2) | Significant improvement in visual and textual understanding and reasoning. |
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