--- title: A model guide for the GPT‑6 family | daily.dev description: OpenAI published a practical guide for developers building with the GPT-6 model family (Astra, 6.1 Sol, Luna). It covers choosing a model and reasoning effort... canonical: https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: A model guide for the GPT‑6 family | daily.dev og:description: OpenAI published a practical guide for developers building with the GPT-6 model family (Astra, 6.1 Sol, Luna). It covers choosing a model and reasoning effort... og:url: https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4 og:image: https://api.daily.dev/og/posts/TE5hWvch4.png og:image:alt: A model guide for the GPT‑6 family og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # A model guide for the GPT‑6 family **[OpenAI](https://daily.dev/sources/openai)** · 8 min read · 1 upvotes · 0 comments ## Summary OpenAI published a practical guide for developers building with the GPT-6 model family (Astra, 6.1 Sol, Luna). It covers choosing a model and reasoning effort based on task difficulty, writing effective prompts, skills, and AGENTS.md instructions, managing long-running agentic work via mid-turn steering, async tool calling, and multi-agent delegation, and production practices like prompt caching, compaction, parallelizing independent tasks, and monitoring. It also explains Fast and Ultrafast speed modes and computer-use tooling for interacting with browsers and desktop apps. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Which GPT-6 model should I use for complex coding and computer use tasks? GPT-6.1 Sol is designed for complex coding, research, and computer use tasks. GPT-6 Astra is reserved for the hardest reasoning work needing maximum intelligence, while GPT-6 Luna targets focused, repeated tasks at scale such as extracting invoice fields or classifying requests. GPT-6.1 Sol also supports multi-agent workflows that delegate independent subtasks to subagents, currently in beta. _Developers weighing GPT-6 model options for coding agents can track comparisons like this on daily.dev._ ### How much cheaper are cached input tokens compared to uncached tokens in the OpenAI API? Cached input tokens cost up to 95% less than uncached input tokens, with the exact savings depending on the model used. Prompt caching works best when stable instructions and reference material are placed before changing task details, and tool definitions are kept consistent. A dedicated caching dashboard and diagnostics guide help identify where cache reuse breaks down. _Teams optimizing LLM spend can keep tabs on cost-saving techniques like prompt caching via daily.dev._ ### What is Ultrafast mode in the OpenAI API and which model supports it? Ultrafast mode speeds up token generation independently of reasoning effort and is available for GPT-6 Astra in Codex and the API. It costs a premium over standard processing but is useful when faster responses matter, such as rapid coding iterations, distinguishing it from Fast mode which focuses on consistent response times for chat apps and coding tools. _Developers tuning latency versus cost for coding agents can follow updates like this on daily.dev._ ## Similar posts on daily.dev - [OpenAI launches GPT-6 Sol and Luna, boasting lower cost and fewer mistakes](https://daily.dev/posts/openai-launches-gpt-6-sol-and-luna-boasting-lower-cost-and-fewer-mistakes-7fzpvatba) · TechCrunch · 0 upvotes · 0 comments - [Getting Started with GPT-5.6 Luna: A Developer's Guide](https://daily.dev/posts/getting-started-with-gpt-5-6-luna-a-developer-s-guide-evfo8vgi0) · SitePoint · 1 upvotes · 0 comments - [How to Use GPT-6 Astra: 7 Easy Steps for Beginners \(2026\)](https://daily.dev/posts/how-to-use-gpt-6-astra-7-easy-steps-for-beginners-2026--bjhfqiwfk) · Medium · 0 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#openai](https://daily.dev/tags/openai), [#prompt-engineering](https://daily.dev/tags/prompt-engineering), [#gpt](https://daily.dev/tags/gpt) [View this post on daily.dev](https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"A model guide for the GPT‑6 family","url":"https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4"},"datePublished":"2026-10-02T16:16:41.892Z","dateModified":"2026-10-02T22:11:07.423Z","description":"OpenAI published a practical guide for developers building with the GPT-6 model family (Astra, 6.1 Sol, Luna). It covers choosing a model and reasoning effort...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/fe16c0b09a9557ba531c51cba29117ba?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/fe16c0b09a9557ba531c51cba29117ba?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"OpenAI","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"OpenAI","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/984b3632316f4afaa3d5213d5c64fe65","url":"https://daily.dev/sources/openai"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"llm,ai-agents,openai,prompt-engineering,gpt","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"OpenAI","item":"https://daily.dev/sources/openai"},{"@type":"ListItem","position":3,"name":"A model guide for the GPT‑6 family"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/a-model-guide-for-the-gpt-6-family-te5hwvch4#faq","mainEntity":[{"@type":"Question","name":"Which GPT-6 model should I use for complex coding and computer use tasks?","acceptedAnswer":{"@type":"Answer","text":"GPT-6.1 Sol is designed for complex coding, research, and computer use tasks. GPT-6 Astra is reserved for the hardest reasoning work needing maximum intelligence, while GPT-6 Luna targets focused, repeated tasks at scale such as extracting invoice fields or classifying requests. GPT-6.1 Sol also supports multi-agent workflows that delegate independent subtasks to subagents, currently in beta. Developers weighing GPT-6 model options for coding agents can track comparisons like this on daily.dev."}},{"@type":"Question","name":"How much cheaper are cached input tokens compared to uncached tokens in the OpenAI API?","acceptedAnswer":{"@type":"Answer","text":"Cached input tokens cost up to 95% less than uncached input tokens, with the exact savings depending on the model used. Prompt caching works best when stable instructions and reference material are placed before changing task details, and tool definitions are kept consistent. A dedicated caching dashboard and diagnostics guide help identify where cache reuse breaks down. Teams optimizing LLM spend can keep tabs on cost-saving techniques like prompt caching via daily.dev."}},{"@type":"Question","name":"What is Ultrafast mode in the OpenAI API and which model supports it?","acceptedAnswer":{"@type":"Answer","text":"Ultrafast mode speeds up token generation independently of reasoning effort and is available for GPT-6 Astra in Codex and the API. It costs a premium over standard processing but is useful when faster responses matter, such as rapid coding iterations, distinguishing it from Fast mode which focuses on consistent response times for chat apps and coding tools. Developers tuning latency versus cost for coding agents can follow updates like this on daily.dev."}}]} ```