GPT-4 vs GPT-4o (2026)
Should you switch from GPT-4 to GPT-4o? GPT-4o is faster, cheaper, and scores higher on every major benchmark. Here's the full comparison — and why there's really no debate.
GPT-4o is a strict upgrade. It's faster, 4x cheaper, has a 16x larger context window, scores higher on coding and math benchmarks, and handles multimodal inputs natively. There is no meaningful reason to choose legacy GPT-4 — OpenAI itself is deprecating it.
Category Breakdown
GPT-4o costs $2.50/1M input tokens. Legacy GPT-4 Turbo costs $10.00/1M — 4x more expensive. The original GPT-4 8K was even pricier at ~$30/1M. GPT-4o delivers better performance for a fraction of the cost.
GPT-4o is significantly faster with lower latency across all request types. GPT-4 was notoriously slow at launch. GPT-4o's architecture improvements deliver near-instant responses even for complex prompts.
GPT-4o has a 128K token context window. The original GPT-4 had just 8K tokens (32K for the turbo variant). GPT-4o can process an entire novel or large codebase in a single prompt.
GPT-4o scores 90.2% on HumanEval. The original GPT-4 scored approximately 67% when it launched. A massive improvement driven by better training data and architecture refinements.
GPT-4o scores 76.6% on the MATH benchmark vs GPT-4's ~52% at launch. For quantitative tasks and multi-step reasoning, GPT-4o is dramatically more capable.
GPT-4o was built as a true omnimodal model from the start — it natively processes text, images, and audio in one unified model. GPT-4 added vision later as a separate capability bolt-on.
GPT-4o scores 88.7% on MMLU vs GPT-4's original ~87%. Both are strong, but GPT-4o has improved across the board since GPT-4 launched.
OpenAI has been deprecating legacy GPT-4 endpoints. GPT-4o is the actively maintained model receiving updates. Using legacy GPT-4 in production means running on a model that will eventually be shut down.
Neither GPT-4 nor GPT-4o generates images natively — DALL-E 3 is a separate model in ChatGPT. Both can reference or discuss images when given as input.
Both GPT-4 Turbo and GPT-4o support fine-tuning via the OpenAI API. The process and pricing are similar, though GPT-4o's fine-tuning produces better results as a starting point.
Specs at a Glance
| GPT-4 (legacy) | GPT-4o | |
|---|---|---|
| Context window | 8K – 32K tokens | 128K tokens |
| API input price | ~$10–30 / 1M | $2.50 / 1M |
| API output price | ~$30–60 / 1M | $10.00 / 1M |
| HumanEval (coding) | ~67% | 90.2% |
| MATH benchmark | ~52% | 76.6% |
| MMLU benchmark | ~87% | 88.7% |
| Multimodal | Vision add-on | Native (text+image+audio) |
| Speed | Slow | Fast |
| Status | Deprecated | Actively maintained |
Should You Migrate from GPT-4 to GPT-4o?
- You'll immediately save 75%+ on API costs with no change to your prompt structure
- Responses are significantly faster, improving user experience in production apps
- GPT-4o scores higher on coding and reasoning benchmarks — better output quality
- The 128K context window removes the need to chunk large documents
- OpenAI is sunsetting legacy GPT-4 endpoints — migration is inevitable
Related comparisons
Compare all AI models
See the full picture — pricing, benchmarks, and capabilities across 15 models.
Full Comparison Table →