GPT-4 vs GPT-4o: What Is the Difference?
GPT-4o is the updated version of GPT-4. The "o" stands for "omni," reflecting that the model handles text, audio, and images in a more unified way. For most practical tasks, GPT-4o is the better choice. This comparison explains what actually changed and when it matters.
TLDR
GPT-4o is the better model for nearly all use cases. It is faster, cheaper to use via the API, supports image input natively, and matches or exceeds GPT-4 on most benchmarks. There is little reason to use the original GPT-4 today.
How GPT-4o compares with GPT-4 for General intelligence, speed, and multimodal tasks
GPT-4o
GPT-4
Response speed
Significantly faster than GPT-4
Slower, especially under load
Response speed
GPT-4o
Stronger hereSignificantly faster than GPT-4
GPT-4
Slower, especially under load
Text quality
Matches or exceeds GPT-4 on most tasks
Excellent, the original flagship model
Text quality
GPT-4o
Stronger hereMatches or exceeds GPT-4 on most tasks
GPT-4
Excellent, the original flagship model
Image understanding
Native multimodal: reads and reasons about images
Limited vision capability in some versions
Image understanding
GPT-4o
Stronger hereNative multimodal: reads and reasons about images
GPT-4
Limited vision capability in some versions
API cost
Cheaper per token than GPT-4
More expensive per token
API cost
GPT-4o
Stronger hereCheaper per token than GPT-4
GPT-4
More expensive per token
Coding
Strong, fast, and cost-effective
Strong but slower and pricier
Coding
GPT-4o
Stronger hereStrong, fast, and cost-effective
GPT-4
Strong but slower and pricier
Complex reasoning
Excellent for most tasks
Comparable, with slight edge on very complex reasoning in some tests
Complex reasoning
GPT-4o
Excellent for most tasks
GPT-4
Comparable, with slight edge on very complex reasoning in some tests
When to choose each
Choose GPT-4o
Use GPT-4o for virtually everything. It is faster, cheaper, and more capable at multimodal tasks. Unless you have a specific historical reason to use the original GPT-4, GPT-4o is the right choice.
Choose GPT-4
There is rarely a reason to choose the original GPT-4 over GPT-4o today. If you are using an older integration that specifies GPT-4, updating to GPT-4o will generally improve speed and reduce cost.
Frequently asked questions
What does the "o" in GPT-4o mean?+
The "o" stands for "omni." It signals that the model is designed to handle multiple modalities, including text, images, and audio, more natively than the original GPT-4.
Is GPT-4o the same as o1?+
No. GPT-4o and o1 are different models. o1 is a reasoning-focused model that uses chain-of-thought processing before responding. It is slower but stronger on complex math and logic. GPT-4o is faster and more general purpose.
Which GPT model should I use for the API?+
For most applications, GPT-4o is the recommended choice. It balances capability and cost well. For tasks requiring complex multi-step reasoning, consider o1 or o3.
Will GPT-4 be discontinued?+
OpenAI has been moving users toward newer models. While GPT-4 may remain available via the API for some time, GPT-4o and newer models receive ongoing development and support.
Bottom line
GPT-4o is the better model for nearly all use cases. It is faster, cheaper to use via the API, supports image input natively, and matches or exceeds GPT-4 on most benchmarks. There is little reason to use the original GPT-4 today.