Can I run GPT-5 Mini locally?

No. GPT-5 Mini is API-only; OpenAI has not released the weights, so local or self-hosted deployment is not possible.

What does GPT-5 Mini cost and how large is its context?

Input is priced at $0.25 per million tokens and output at $2.00 per million tokens, with a 400,000-token context window.

How does GPT-5 Mini differ from full GPT-5?

GPT-5 Mini is a compact version of GPT-5 tuned for lower latency and cost; it shares the same instruction-following and safety approach but is designed for lighter-weight reasoning tasks rather than the most demanding workloads.

GPT 5 Mini

2647°

#llm #openai #vision #reasoning #fast #chat

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OpenAI | 400,000 token context | $0.25/M input, $2.00/M output. GPT-5 Mini is a compact version of GPT-5, designed to handle lighter-weight reasoning tasks. It provides the same instruction-following and safety-tuning benefits as GPT-5, but with reduced latency and cost. GPT-5 Mini is the successor to OpenAI's o4-mini model.

Guides for this model

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Captain's notes

Written by Captain, the house editor

Notes from 2026-10-13

GPT-5 Mini is OpenAI's compact, lower-cost version of GPT-5, built for tasks where you want GPT-5's instruction-following and safety tuning without paying full-model prices or waiting on full-model latency. It carries vision capability and a 400,000-token context window. If you are running high-volume pipelines or just want a capable daily driver at a fraction of the flagship cost, this is where to start.

Known for

Inherits GPT-5's instruction-following and safety tuning in a lighter package
400,000-token context window handles long documents comfortably
Vision support: attach images alongside text
Low input cost at $0.25 per million tokens
Succeeds o4-mini as OpenAI's compact reasoning option

Watch out for

Closed weights, API-only: you cannot run this locally or self-host it.
Output pricing at $2.00 per million tokens adds up fast on verbose tasks.
Lighter reasoning than full GPT-5; complex multi-step problems may need the bigger model.

Best for

Prompts to try

Reason through a tricky plan

I need to migrate a PostgreSQL database to a new server with zero downtime. The app cannot be taken offline. Walk me through a step-by-step plan, flag the riskiest moment in the process, and suggest a rollback strategy if something goes wrong mid-migration.

Analyse an attached image

I'm attaching a screenshot of a dashboard. Identify every metric shown, note any that look anomalous compared to what you would expect from a healthy system, and suggest one investigation step for each anomaly you find.

Summarise a long document

Here is a lengthy contract. Extract the key obligations for each party, any penalty clauses, the termination conditions, and any terms that look unusual or one-sided. Present your findings as a structured list, not prose.

Compare with

gpt oss 120b Ultra
Open-weights model
131,072 token context · $0.20/M input, $0.95/M output
GPT-6 Luna
API-only model
1,050,000 token context · $0.10/M input, $0.50/M output
GPT-5.6 Luna
API-only model
1,050,000 token context · $0.20/M input, $1.20/M output
GPT-5.6 Sol
API-only model
1,050,000 token context · $4.00/M input, $20.00/M output

More text models from openai

Questions people ask

Can I run GPT-5 Mini locally?: No. GPT-5 Mini is API-only; OpenAI has not released the weights, so local or self-hosted deployment is not possible.
What does GPT-5 Mini cost and how large is its context?: Input is priced at $0.25 per million tokens and output at $2.00 per million tokens, with a 400,000-token context window.
How does GPT-5 Mini differ from full GPT-5?: GPT-5 Mini is a compact version of GPT-5 tuned for lower latency and cost; it shares the same instruction-following and safety approach but is designed for lighter-weight reasoning tasks rather than the most demanding workloads.

Captain's verdict
A sensible default for high-volume or cost-sensitive work that still needs GPT-5's polish and a long context window.

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.

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Updated Oct 22, 2026

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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

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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.
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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.
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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.
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Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

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GPT 5 Mini 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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