GPT 4o (2024 11 20)
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OpenAI | 128,000 token context | $2.50/M input, $10.00/M output. The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded files, providing deeper insights & more thorough responses. GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of GPT-4 Turbo while being twice as fast and 50% more cost-effective. GPT-4o also offers improved performance in processing non-English languages and enhanced visual capabilities.
Guides for this model
Open weights vs open source vs API-only: what you are actually allowed to do
The 10 cheapest ChatGPT alternatives in 2026: free local models, free tiers and flat-rate plans
Captain's notes
Notes from 2026-10-13
GPT-4o (2024-11-20) is OpenAI's omni model, handling both text and image inputs with a 128,000-token context window. This November snapshot sharpens creative writing noticeably and improves file analysis, while keeping the speed and cost advantages over GPT-4 Turbo. It suits writers, analysts and anyone who regularly works with documents or mixed media.
Known for
- Stronger creative writing: more natural tone, better tailored to context and audience.
- Deeper file analysis with more thorough responses on uploaded documents.
- Accepts image inputs alongside text, useful for visual tasks.
- Better non-English language handling than earlier GPT-4 class models.
- Faster and cheaper than GPT-4 Turbo at comparable intelligence.
Watch out for
- Closed weights, API-only: you cannot run this locally or inspect the model.
- Output costs $10 per million tokens, which adds up fast on long generative tasks.
- Context tops out at 128,000 tokens; not an option for very long document work.
Prompts to try
Rewrite for a new audience
Here is a technical explanation written for engineers. Rewrite it for a general audience with no technical background, keeping it accurate but making it engaging and easy to follow. Aim for roughly the same length.
[paste your text here]
Analyse an uploaded document
I'm attaching a report. Read it carefully and give me: the three most important findings, any claims that seem weakly supported, and two questions I should ask the authors before acting on this.
Describe and interpret an image
I'm attaching an image. Describe what you see in detail, then tell me what you think is the most interesting or unusual thing about it and why.
Compare with
- GPT-4o-miniAPI-only model128,000 token context · $0.15/M input, $0.60/M output
- GPT-5 Image MiniAPI-only model400,000 token context · $2.50/M input, $2.00/M output
- GPT-4oAPI-only model128,000 token context · $2.50/M input, $10.00/M output
- GPT-4o-mini (2024-07-18)API-only model128,000 token context · $0.15/M input, $0.60/M output
More text models from openai
Questions people ask
- Can I run GPT-4o 2024-11-20 locally?
- No. OpenAI has not released weights for any GPT-4o version; it is available only through the API or ChatGPT.
- What does GPT-4o 2024-11-20 cost and what is the context window?
- Pricing is $2.50 per million input tokens and $10.00 per million output tokens, with a 128,000-token context window.
- What is different about the 2024-11-20 version compared to earlier GPT-4o snapshots?
- OpenAI specifically improved creative writing quality and the model's ability to work with uploaded files, producing deeper insights and more thorough responses.
Captain's verdictA solid all-rounder if you need polished writing and file analysis via API, but the output price demands you keep responses tight.
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
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Also ranked: #85 Hottest Text / LLM text model
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How this score adds up
This model has no popularity data from any source yet, so it carries a stand-in number below 7,000° that keeps the lists complete. It never ranks above a model with data. The breakdown appears here as soon as a source reports it.
Glossary: the terms used here
- Heat score
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- Floor
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- Download-equivalents
- Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
- Log scale
- Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
- Likes
- Thumbs up and likes from every source, worth half a download each on the log scale.
- Adoption rate
- How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
- Measured and estimated
- Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
- Seeder
- Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
- AI Horde
- A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
- Generation sites
- Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
- OpenRouter tokens
- A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
- Full model (checkpoint)
- The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
- LoRA and embedding
- Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
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- Age
- Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
- Family boost
- A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
- Stand-in score
- A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
- New! (grace period)
- A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
- Trend
- How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
- Typical model
- The middle of the catalog: half the models with a figure grew faster over the period, half slower.
GPT 4o (2024 11 20) is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models and check its heat score to see how it is trending.
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