GPT-4o vs GPT-4: Differences, Pricing & 2026 Status

GPT-4o is OpenAI’s faster, cheaper, natively multimodal model released May 13, 2024, while GPT-4 is the March 14, 2023 text-focused model it replaced. Both are now retired from the ChatGPT consumer app — GPT-4 left on April 30, 2025, and GPT-4o followed on February 13, 2026 — yet both remain reachable through the OpenAI API today. GPT-4o processes text, images, and audio in a single neural network at roughly $2.50 per 1M input tokens and $10 per 1M output tokens, against GPT-4’s text-only design at $30 per 1M input tokens and $60 per 1M output tokens.

This guide compares their features, benchmarks, pricing, and real-world reception, including the unusually emotional backlash that followed GPT-4o’s ChatGPT retirement. For a broader view of OpenAI’s current lineup, see OpenAI Models Guide.

Quick Comparison Table

GPT-4o beats GPT-4 on speed, cost, and multimodal range, while GPT-4’s only structural advantage today is a longer track record in production systems. The table below lines up the specifications that matter most for a migration or model-selection decision. For a related comparison, see GPT-4 vs GPT-3.5 Comparison.

Specification	GPT-4o	GPT-4
Developer	OpenAI	OpenAI
Release date	May 13, 2024	March 14, 2023
Context window	128,000 tokens	8,192 tokens
Max output tokens	16,384 tokens	8,192 tokens
Knowledge cutoff	October 2023	December 2023
Input modalities	Text, image, audio	Text only (vision in separate snapshots)
API input price	$2.50 per 1M tokens	$30 per 1M tokens
API output price	$10 per 1M tokens	$60 per 1M tokens
Average response latency	About 320 milliseconds	About 5 seconds
Retired from ChatGPT app	Yes, February 13, 2026	Yes, April 30, 2025
Available via API today	Yes, current general model	Yes, until October 23, 2026

What Is GPT-4o?

GPT-4o is OpenAI’s “omni” model, released May 13, 2024, built as a single neural network trained end-to-end across text, vision, and audio rather than stitching separate models together. That native design lets GPT-4o listen, see, and respond inside one system instead of routing audio through a separate speech model and images through a separate vision model, the approach GPT-4 relied on inside ChatGPT. OpenAI reported GPT-4o matches GPT-4 Turbo’s text and reasoning quality while responding roughly twice as fast and scoring 88.7% on the MMLU benchmark, versus GPT-4 Turbo’s 86.5%.

Its Advanced Voice Mode processes speech directly, supporting full-duplex conversation where the model can be interrupted mid-sentence, a capability GPT-4 never had. GPT-4o briefly disappeared from ChatGPT’s model picker in August 2025 during OpenAI’s GPT-5 rollout, was restored for paid subscribers within 24 hours after user backlash, and was then permanently retired from the ChatGPT app on February 13, 2026.

What Is GPT-4?

GPT-4 is OpenAI’s fourth-generation language model, released March 14, 2023, built for deeper reasoning and higher factual accuracy than GPT-3.5 rather than for multimodal input. Its base API version runs on an 8,192-token context window, though OpenAI later shipped GPT-4 Turbo with a 128,000-token window and vision support as a separate, faster snapshot. GPT-4 is text-only at its core: within ChatGPT, it had to call separate OpenAI systems, such as DALL-E for image generation and Whisper for speech recognition, to handle non-text input. OpenAI retired GPT-4 from the ChatGPT app on April 30, 2025 in favor of GPT-4o, and — see GPT-4 vs GPT-3.5 for how it compared to its own predecessor — its remaining API access, priced at $30 per 1M input tokens and $60 per 1M output tokens, is scheduled to end on October 23, 2026.

Feature Comparison

GPT-4o and GPT-4 diverge on five core features: multimodal input, context window, speed, language handling, and coding reliability. Each affects a different class of workload, from live voice assistants to long-document review.

Multimodal and Voice Capabilities

GPT-4o accepts text, images, and audio as native input, while GPT-4 processes text only at its core, with image understanding limited to separate vision snapshots. GPT-4o’s Advanced Voice Mode supports full-duplex audio, meaning it can listen and speak simultaneously and respond to tone, pacing, and interruptions in near real time. GPT-4 has no equivalent voice capability; ChatGPT’s older voice feature transcribed speech to text with Whisper, ran it through GPT-4, then converted the reply back to speech, adding noticeable latency at every step.

Context Window and Output Length

GPT-4o’s 128,000-token context window is 15.6 times larger than GPT-4’s base 8,192-token window, and its 16,384-token maximum output doubles GPT-4’s 8,192-token limit. A larger context window lets a model track more source material in a single request, useful for tasks such as reviewing a long contract or holding an extended multi-turn conversation without losing earlier details. GPT-4 Turbo closed part of this gap with its own 128,000-token window, but the original GPT-4 model most legacy integrations still call keeps the smaller limit.

Speed and Latency

GPT-4o responds roughly 15 times faster than GPT-4, averaging around 320 milliseconds compared to GPT-4’s roughly 5-second average reply time. That speed difference comes from GPT-4o’s more efficient, natively multimodal architecture, which needs less computation per token than GPT-4’s original design. For latency-sensitive products, examples include live customer-support chat and voice assistants, GPT-4o’s response time makes real-time interaction feasible in a way GPT-4 never supported well.

Language and Tokenization

GPT-4o handles non-Western-alphabet languages, examples include Chinese, Hindi, and Korean, more efficiently than GPT-4 due to an improved tokenizer. A more efficient tokenizer breaks text for these languages into fewer tokens per word, which lowers both API cost and processing time for non-English workloads. GPT-4 uses an older tokenizer that splits these languages into more tokens for the same text, making high-volume multilingual use measurably more expensive.

Coding Ability

GPT-4o matches or slightly exceeds GPT-4 Turbo’s coding reliability across common languages such as Python, JavaScript, and SQL, while responding faster on the same task. Both models handle multi-function code generation and debugging more reliably than GPT-3.5, but GPT-4o’s speed advantage matters directly in interactive coding assistants, examples include IDE autocomplete tools and pair-programming chat, where response latency affects usability as much as raw accuracy.

Performance Comparison

GPT-4o outperforms GPT-4 on published benchmarks while responding faster, leaving GPT-4 with no clear performance advantage left in 2026. This is a departure from typical model trade-offs, where a faster, cheaper option usually sacrifices some accuracy.

Benchmark Performance

GPT-4o scores 88.7% on the MMLU general-knowledge benchmark, a 2.2-percentage-point improvement over GPT-4 Turbo’s 86.5%, while matching or exceeding original GPT-4 on reasoning and coding evaluations. OpenAI’s own testing found GPT-4o reaches GPT-4 Turbo-level performance on text and reasoning tasks while substantially improving vision and audio understanding, benchmarks original GPT-4 was never evaluated against since it lacks native audio input.

Real-World Reasoning

Independent head-to-head evaluations found GPT-4o consistently outperforming GPT-4 on writing, coding, and STEM tasks, according to comparison testing cited by outlets covering OpenAI’s April 2025 GPT-4 retirement announcement. The gap is narrow on straightforward text reasoning, where both models handle multi-step instructions competently, but widens on any task involving an image, a voice interaction, or a non-English language. For a related comparison, see AI Comparison.

Pricing

GPT-4 costs 12 times more than GPT-4o on input tokens and 6 times more on output tokens through the OpenAI API. Both models bill per token, split between input tokens (the prompt sent) and output tokens (the response generated).

Model	Input (per 1M tokens)	Output (per 1M tokens)	Context window
GPT-4o	$2.50	$10.00	128,000 tokens
GPT-4	$30.00	$60.00	8,192 tokens

GPT-4o’s price dropped from its August 2024 launch rate as OpenAI’s pricing has shifted over time, but it has consistently stayed a fraction of GPT-4’s per-token cost since release. Neither model is billed inside a consumer ChatGPT subscription anymore, since both were removed from the app’s model picker; the rates above apply to direct API usage only. A high-volume workload, examples include chatbot support and document summarization, is rarely justified on GPT-4 today given GPT-4o’s lower cost and higher benchmark scores at the same or better speed.

Pros and Cons

GPT-4o wins on nearly every axis except institutional track record, while GPT-4 survives mainly in legacy integrations that haven’t been migrated yet.

GPT-4o Pros and Cons

7 factors define GPT-4o’s trade-off profile:

• Pro: Native text, image, and audio input in a single model.
• Pro: Roughly 15 times faster average response time than GPT-4.
• Pro: 12 times cheaper input tokens and 6 times cheaper output tokens.
• Pro: 128,000-token context window versus GPT-4’s 8,192 tokens.
• Pro: Higher MMLU benchmark score than GPT-4 Turbo.
• Con: No longer selectable inside the ChatGPT consumer app as of February 13, 2026.
• Con: Its exact successor path (GPT-5-family models) still unsettles users attached to its conversational tone.

GPT-4 Pros and Cons

6 factors define GPT-4’s trade-off profile:

• Pro: Longer production track record across enterprise integrations built since 2023.
• Pro: December 2023 knowledge cutoff, slightly newer than GPT-4o’s October 2023 cutoff.
• Con: Costs 12 times more per input token than GPT-4o.
• Con: No native image or audio input at its core.
• Con: Smaller 8,192-token context window.
• Con: Scheduled for full API shutdown on October 23, 2026.

User Reviews

Developer feedback treats GPT-4o as the clear technical upgrade, but GPT-4o’s February 2026 ChatGPT retirement triggered an unusually emotional backlash that GPT-4’s 2025 retirement never saw. On developer forums, the consistent complaint about GPT-4 was response latency and cost under sustained use, exactly the two problems GPT-4o was built to fix. GPT-4o’s removal was different: Reddit threads with hundreds of comments compared losing access to it to “losing a trusted friend,” a Change.org petition to restore it reached close to 21,000 signatures, and a #keep4o campaign spread across social media from users who described GPT-4o’s warmer, more validating conversational tone as something GPT-5-family models don’t replicate.

That reaction reflects real product attachment rather than a technical complaint, and it is worth knowing about before assuming GPT-4o’s retirement will pass as quietly as GPT-4’s did. For a related comparison, see GPT-4o vs GPT-4.1.

Use Cases

GPT-4o fits nearly every workload GPT-4 used to handle, plus multimodal and voice tasks GPT-4 was never built for. Matching the model to the task still matters even though GPT-4o wins on cost and speed.

When to Choose GPT-4o

Choose GPT-4o for:

• Any task that combines text with images or audio, examples include document scanning and voice assistants.
• Real-time or latency-sensitive applications, examples include live chat widgets and interactive coding tools.
• High-volume workloads where per-token cost affects the overall budget.
• Multilingual products serving non-Western-alphabet languages.

When to Choose GPT-4

Choose GPT-4 for:

• Legacy integrations built before GPT-4o’s release that haven’t been migrated yet.
• Systems pinned to GPT-4’s exact output behavior for regression-testing reasons.
• Short-term use before the October 23, 2026 API shutdown, with a migration already planned.

Final Recommendation

Choose GPT-4o for nearly all new work, and treat GPT-4 as a legacy option to migrate away from before its October 23, 2026 API shutdown.

Choose GPT-4o if:
– The task involves images, audio, or a non-English language alongside text.
– Response speed and per-token cost both matter to the product.
– The integration is new or already scheduled for a model upgrade.

Choose GPT-4 if:
– An existing system depends on GPT-4’s specific output behavior and hasn’t been re-tested against a newer model yet.
– The workload is temporary and already has a migration plan in place before October 2026.

Both paths point toward the same current-generation lineup: since GPT-4o itself was retired from ChatGPT in February 2026, teams standardizing on one model today should evaluate OpenAI’s GPT-5 family directly — GPT-5 vs GPT-5 Mini breaks down that current entry-tier choice.

Alternatives

GPT-5-family models, Claude, and Gemini are the main alternatives to GPT-4o and GPT-4 today. OpenAI’s GPT-5 family replaced both models inside ChatGPT and extends GPT-4o’s multimodal design with stronger reasoning. Outside OpenAI, Claude vs ChatGPT and Gemini vs ChatGPT compare the two other frontier providers most commonly evaluated alongside OpenAI’s models. For a side-by-side view across every major provider rather than just OpenAI’s own history, see our Best AI Chatbot and Best AI Models guides.

FAQ

What Is the Difference Between GPT-4 and GPT-4o?

GPT-4o adds native image and audio input, a 128,000-token context window, and roughly 15 times faster responses compared to GPT-4’s text-only, 8,192-token design. GPT-4o also costs a fraction of GPT-4’s per-token price: $2.50 versus $30 per 1M input tokens, and $10 versus $60 per 1M output tokens.

Is GPT-4o Still Available in ChatGPT?

No, GPT-4o is not available in the ChatGPT app — OpenAI retired it from the consumer product on February 13, 2026, after briefly restoring it for paid subscribers during a similar scare in August 2025. It remains accessible through the OpenAI API.

Why Did GPT-4o’s Retirement Cause So Much Backlash?

Many users had built an ongoing, personal conversational habit around GPT-4o’s warmer tone, and its removal felt like losing that relationship rather than losing a tool. Reddit threads describing the loss as “grief,” a #keep4o social media campaign, and a Change.org petition nearing 21,000 signatures followed the February 13, 2026 retirement — a far larger reaction than GPT-4’s own ChatGPT retirement drew in April 2025.

Can I Still Use GPT-4 or GPT-4o Through the API?

Yes, both remain available through the OpenAI API as of this writing, though on different timelines. GPT-4o continues as a current general-release API model with no announced shutdown date, while GPT-4 and its snapshots are scheduled for removal from the API on October 23, 2026.

How Much Faster Is GPT-4o Than GPT-4?

GPT-4o responds in about 320 milliseconds on average, compared to roughly 5 seconds for GPT-4 — close to 15 times faster. OpenAI attributes the gap to GPT-4o’s more efficient, natively multimodal architecture, which requires less computation per generated token.

What Should I Migrate to Before GPT-4 Shuts Down?

OpenAI recommends GPT-4o or a current GPT-5-family model as GPT-4’s direct replacement, since both outperform original GPT-4 on published benchmarks at a lower per-token cost. The OpenAI Models Guide breaks down which current model fits which budget and workload.

Final Verdict

GPT-4o wins on nearly every measurable dimension — speed, cost, context window, and multimodal range — while GPT-4 remains relevant only to legacy systems racing a hard October 23, 2026 API shutdown deadline. Neither model is selectable inside ChatGPT anymore, so the practical decision for new projects isn’t really GPT-4o versus GPT-4; it’s how quickly to move off both onto OpenAI’s current GPT-5-family lineup. Teams maintaining older integrations should treat this comparison as a migration checklist: confirm which model ID a system calls, weigh GPT-4o’s cost and speed advantages against any regression risk, and complete the switch before GPT-4’s API access ends.