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Captain's notes
Notes from 2026-10-13
GPT OSS 120B Turbo is OpenAI's large-scale reasoning model served via API, positioned at a notably low price point for its class. At $0.15 per million input tokens it undercuts most frontier-tier offerings considerably, while the 131,072-token context handles substantial documents and multi-turn work. It suits developers and researchers who need serious reasoning capacity without paying frontier prices.
Known for
- Reasoning-class capability at a price well below typical frontier models
- 131,072-token context window handles long documents and extended conversations
- Very low input cost at $0.15 per million tokens
- Built for API integration rather than consumer chat interfaces
Watch out for
- Weights are closed; you cannot run this locally or inspect what you are using.
- OpenAI has published no model card details, so architecture and training data are unknown.
- API-only access means your data leaves your infrastructure on every call.
Prompts to try
Multi-step logic problem
A farmer has 17 sheep. All but 9 die. How many are left? Now extend the puzzle: if each surviving sheep produces 3 lambs and the farmer sells half the total flock, how many animals remain? Show your reasoning step by step before giving the final answer.
Analyse a long document
I am going to paste a lengthy contract below. Read it carefully, then list every clause that creates an obligation on the buyer, every clause that limits liability, and any terms that could be considered unusual or one-sided. Organise your findings under those three headings.
Research synthesis task
Explain the core disagreement between frequentist and Bayesian statisticians, give a concrete example where each approach produces a different practical recommendation, and assess which framework is better suited to small-sample medical trials and why.
Compare with
- GPT-6 AstraAPI-only model1,050,000 token context · $10.00/M input, $50.00/M output
- GPT-6 Luna ProAPI-only model1,050,000 token context · $0.10/M input, $0.50/M output
- GPT-5.6 Luna ProAPI-only model1,050,000 token context · $0.20/M input, $1.20/M output
- GPT-6.1 Sol ProAPI-only model1,050,000 token context · $2.00/M input, $10.00/M output
More text models from openai
Questions people ask
- Can I run GPT OSS 120B Turbo locally?
- No. The weights are closed and there is no Hugging Face repository; you access it through OpenAI's API only.
- What does it cost and how long is the context?
- Pricing is $0.15 per million input tokens and $0.60 per million output tokens, with a 131,072-token context window.
- How does this differ from other OpenAI models?
- OpenAI has not published a model card, so a precise comparison is not possible; the 'Turbo' naming and low price point suggest it is optimised for cost-efficient reasoning at scale rather than maximum capability.
Captain's verdictCheap reasoning at 131k context is a useful combination; the closed weights and absent documentation are the price you pay.
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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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
- One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
- Floor
- The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
- 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.
- Family and weights
- The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
- 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 oss 120b Turbo 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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