Comparison · Updated Aug 24, 2026

GPT-4 vs GPT-4o

Comparison of OpenAI's GPT-4 (2023) and GPT-4o (2024): release dates, context windows, multimodal features and ideal use cases.

Differences

AttributeGPT-4GPT-4o
DeveloperOpenAIOpenAI
Released2023-03-142024-05-13
Open weightsfalsefalse
Context window8192 tokens128000 tokens
Modalitytext + imagetext + image + audio
Capabilitiesreasoning, multimodal, codingrealtime voice, vision, tool use
Best forreasoning and coding tasks with standard contextreal‑time audio‑visual apps and large‑context tasks

Verdict

GPT-4 suits users needing strong reasoning and coding with a standard context window, while GPT-4o is better for applications requiring real‑time audio‑visual interaction and larger context.

Analysis

Overview GPT-4 and GPT-4o are both large language models developed by OpenAI. GPT-4 was introduced in March 2023 as a multimodal successor to GPT-3.5, adding image understanding to the text‑only capabilities of its predecessor. GPT-4o, released in May 2024, extends the modality set further by incorporating audio processing and emphasizes real‑time interaction. Neither model releases its weights publicly, and both are accessed via OpenAI’s API.

Where they differ The most concrete difference lies in the context window: GPT-4 supports up to 8,192 tokens, whereas GPT-4o expands this to 128,000 tokens, allowing it to handle much longer documents or conversations in a single pass. In terms of modality, GPT-4 processes text and images, while GPT-4o adds native audio understanding, enabling it to listen and respond to spoken input in real time. Capability-wise, GPT-4 is highlighted for strong reasoning, coding assistance, and multimodal understanding. GPT-4o is marketed for real‑time voice interaction, vision tasks, and tool use, suggesting a tighter integration with external functions and lower latency for interactive applications. Both models remain closed‑source, and pricing or licensing details are not part of the supplied facts.

Which to choose Select GPT-4 when the primary workload involves complex reasoning, code generation, or tasks that benefit from a solid multimodal (text‑image) foundation but do not require extremely long contexts or live audio processing. It remains a reliable choice for traditional LLM workloads where latency is less critical. Choose GPT-4o for use cases that demand handling of lengthy inputs, real‑time voice conversations, or seamless tool invocation alongside vision and text. Its larger context window and audio capabilities make it suited for interactive assistants, live transcription‑translation systems, or applications that need to maintain extensive state over extended dialogues.

Frequently asked

What is the main difference between GPT-4 and GPT-4o?
The main difference is the context window and modality support. GPT-4 handles up to 8,192 tokens and processes text and images, while GPT-4o extends the context to 128,000 tokens and adds native audio understanding, enabling real‑time voice interaction alongside vision and text.
Which model has a larger context window?
GPT-4o has the larger context window, supporting up to 128,000 tokens compared to GPT-4’s 8,192 tokens. This allows GPT-4o to work with much longer documents or extended conversations in a single request.
Can GPT-4o process audio?
Yes, GPT-4o includes native audio processing as part of its multimodal design. It can understand spoken input and generate spoken output in real time, a capability not present in GPT-4, which is limited to text and image modalities.
Is GPT-4 still available for use?
GPT-4 remains accessible through OpenAI’s API alongside newer models. Its release date is March 14, 2023, and it continues to be offered for tasks that benefit from its reasoning and coding strengths, even after the introduction of GPT-4o.
Do both models support tool use?
GPT-4o explicitly lists tool use as a capability, indicating tight integration with external functions. GPT-4’s documented capabilities focus on reasoning, multimodal understanding, and coding; tool use is not highlighted in the supplied facts, though developers can still implement tool interaction via prompting or API wrappers.

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