# gpt-6-astra 9

Published articles for gpt-6-astra 9.

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## Generating running routes with GPT-6 Astra and ChatGPT Work

DevFeed: [Generating running routes with GPT-6 Astra and ChatGPT Work](<https://devfeed.tech/articles/generating-running-routes-with-gpt-6-astra-and-chatgpt-work-30507.md>)

Original publisher: [Read original article](<https://simonwillison.net/2026/Sep/12/astra-running-routes/>)

Author: Simon Willison

Published: 2026-09-12T23:56:42Z

Content type: opinion

Language: en

Sources: [Simon Willison](<https://devfeed.tech/sources/simon-willison.md>), [Simon Willison's Weblog](<https://devfeed.tech/sources/simon-willison-s-weblog.md>)

Topics: [ChatGPT](<https://devfeed.tech/topics/chatgpt.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [GeoJSON](<https://devfeed.tech/topics/geojson.md>), [Code](<https://devfeed.tech/topics/code.md>), [d3](<https://devfeed.tech/topics/d3.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-2-235](<https://devfeed.tech/tags/ai-2-235.md>), [chatgpt](<https://devfeed.tech/tags/chatgpt.md>), [chatgpt-204](<https://devfeed.tech/tags/chatgpt-204.md>), [code](<https://devfeed.tech/tags/code.md>), [d3](<https://devfeed.tech/tags/d3.md>), [d3-15](<https://devfeed.tech/tags/d3-15.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [generative-ai-1-981](<https://devfeed.tech/tags/generative-ai-1-981.md>), [geospatial](<https://devfeed.tech/tags/geospatial.md>), [geospatial-85](<https://devfeed.tech/tags/geospatial-85.md>), [gpt](<https://devfeed.tech/tags/gpt.md>), [gpt-6-astra](<https://devfeed.tech/tags/gpt-6-astra.md>), [gpt-6-astra-9](<https://devfeed.tech/tags/gpt-6-astra-9.md>), [llms](<https://devfeed.tech/tags/llms.md>), [llms-1-947](<https://devfeed.tech/tags/llms-1-947.md>), [map](<https://devfeed.tech/tags/map.md>), [openai](<https://devfeed.tech/tags/openai.md>), [openai-463](<https://devfeed.tech/tags/openai-463.md>), [python](<https://devfeed.tech/tags/python.md>), [skills](<https://devfeed.tech/tags/skills.md>), [skills-15](<https://devfeed.tech/tags/skills-15.md>), [work](<https://devfeed.tech/tags/work.md>)

### AI overview

The article describes using ChatGPT Work with GPT-6 Astra to generate 5K and 10K running routes from OpenStreetMap data, producing an embedded visualization and downloadable GPX and GeoJSON files. It also criticizes the lack of visibility into the generated Python code and the loss of that code after thread compaction.

### Source excerpt

Here's a neat thing I had ChatGPT Work with GPT-6 Astra (Max) do this morning: I live at <my address>. Figure out 5K and 10K running routes from me that loop from my house. Use OSM data. It worked for 27 minutes and produced exactly what I'd asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here's that 5K route: When I asked it how it had created the route, it replied: I used Nominatim to locate the address and Overpass to download local OpenStreetMap roads and trails, then calculated the loops locally. Frustratingly, the actual code it ran and exact details of what it did weren't visible to me in the ChatGPT UI. I see this lack of transparency is an anti-feature. By the time I thought to ask for a copy of the Python code it had used, ChatGPT was unable to provide it. This appears to be because the thread had been compacted. I think any LLM system that uses compaction needs to both preserve the pre-compacted text and make that text available via agent tool calls, to protect against this kind of problem. As for displaying the map to me, that used the visualize skill. It created a file called /workspace/el-granada-5k-share.html to embed directly into the ChatGPT UI. Here's a copy of that HTML, which starts like this: <div id="eg-share-loop"> <div class="viz-row"><h3>El Granada harbor loop</h3><span class="text-small">5.1 km</span></div> <div id="eg-share-stage"></div> <div class="text-small text-muted">Map data © <a href="https://www.openstreetmap.org/copyright" target="_blank" rel="noopener">OpenStreetMap contributors</a></div> <style> #eg-share-loop { width:100%; } #eg-share-loop #eg-share-stage { width:100%; margin:8px 0; } #eg-share-loop .eg-share-map { display:block; width:100%; touch-action:none; } #eg-share-loop .eg-share-map text { fill:var(--foreground); font-size:12px; font-weight:400; } #eg-share-loop .eg-share-label { paint-order:stroke; stroke:var(--background); stroke-width:3px; stroke-linejoin:round; } </style> <s

## .blend URL Viewer

DevFeed: [.blend URL Viewer](<https://devfeed.tech/articles/blend-url-viewer-31185.md>)

Original publisher: [Read original article](<https://simonwillison.net/2026/Sep/9/blender-viewer/>)

Author: Simon Willison

Published: 2026-09-09T23:58:32Z

Content type: article

Language: en

Sources: [Simon Willison's Weblog](<https://devfeed.tech/sources/simon-willison-s-weblog.md>)

Topics: [blender](<https://devfeed.tech/topics/blender.md>), [3D](<https://devfeed.tech/topics/3d.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Generative AI](<https://devfeed.tech/topics/generative-ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>), [browser](<https://devfeed.tech/topics/browser.md>)

Tags: [3d](<https://devfeed.tech/tags/3d.md>), [3d-18](<https://devfeed.tech/tags/3d-18.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-2-236](<https://devfeed.tech/tags/ai-2-236.md>), [blender](<https://devfeed.tech/tags/blender.md>), [blender-4](<https://devfeed.tech/tags/blender-4.md>), [codex](<https://devfeed.tech/tags/codex.md>), [codex-57](<https://devfeed.tech/tags/codex-57.md>), [coding-agents](<https://devfeed.tech/tags/coding-agents.md>), [coding-agents-248](<https://devfeed.tech/tags/coding-agents-248.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [generative-ai-1-982](<https://devfeed.tech/tags/generative-ai-1-982.md>), [gpt-6-astra](<https://devfeed.tech/tags/gpt-6-astra.md>), [gpt-6-astra-9](<https://devfeed.tech/tags/gpt-6-astra-9.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [javascript-764](<https://devfeed.tech/tags/javascript-764.md>), [llms](<https://devfeed.tech/tags/llms.md>), [llms-1-948](<https://devfeed.tech/tags/llms-1-948.md>), [tools](<https://devfeed.tech/tags/tools.md>), [tools-78](<https://devfeed.tech/tags/tools-78.md>)

### AI overview

The article presents a .blend URL Viewer built from an existing Blender viewing experiment. It describes using ChatGPT Images 2.5 to generate a Pluribus-themed Fabergé egg image, then using Codex running GPT-6 Astra to create Blender model files that can be viewed in a browser.

### Source excerpt

Tool: .blend URL Viewer I'm continuing to have a lot of fun with GPT-6 Astra and Blender (see my TIL). As a big fan of the Imperial Fabergé Easter eggs, I've always thought it would be fun to make some new ones that celebrate popular culture. Yesterday I decided to try out the new ChatGPT Images 2.5 by running this prompt: Generate a photo of a faberge egg that's themed after the TV show Pluribus - research first It gave me this - honestly not bad for a first attempt! Then, just to see what would happen, I pasted that image into Codex running GPT-6 Astra (high) and prompted: Use your blender local skill to create a blender model of this faverge egg (Here's the skill file, which I created like this.) It churned away for 17m51s and built me several .blend files. I already had this vibe-coded Blender viewing experiment lying around, so I added that to my tools collection and now you can use it to see my Pluribus blender model in your browser: Tags: 3d, javascript, tools, ai, generative-ai, llms, blender, coding-agents, codex, gpt-6-astra

## llm 0.35

DevFeed: [llm 0.35](<https://devfeed.tech/articles/llm-0-35-31182.md>)

Original publisher: [Read original article](<https://simonwillison.net/2026/Sep/7/llm/>)

Author: Simon Willison

Published: 2026-09-07T23:54:54Z

Content type: release

Language: en

Sources: [Simon Willison's Weblog](<https://devfeed.tech/sources/simon-willison-s-weblog.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [gpt-6-astra](<https://devfeed.tech/topics/gpt-6-astra.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>)

Tags: [gpt-6-astra](<https://devfeed.tech/tags/gpt-6-astra.md>), [gpt-6-astra-9](<https://devfeed.tech/tags/gpt-6-astra-9.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llm-631](<https://devfeed.tech/tags/llm-631.md>), [openai](<https://devfeed.tech/tags/openai.md>), [openai-463](<https://devfeed.tech/tags/openai-463.md>), [release](<https://devfeed.tech/tags/release.md>)

### AI overview

llm 0.35 is a release that adds the OpenAI model gpt-6-astra for GPT-6 Astra.

### Source excerpt

Release: llm 0.35 New OpenAI model: gpt-6-astra for GPT-6 Astra. Tags: openai, llm, gpt-6-astra

## The Pelican comparison grid for Astra is pretty interesting

DevFeed: [The Pelican comparison grid for Astra is pretty interesting](<https://devfeed.tech/articles/the-pelican-comparison-grid-for-astra-is-pretty-interesting-30510.md>)

Original publisher: [Read original article](<https://simonwillison.net/2026/Sep/4/astra-pelicans/>)

Author: Simon Willison

Published: 2026-09-04T23:59:05Z

Content type: opinion

Language: en

Sources: [Simon Willison](<https://devfeed.tech/sources/simon-willison.md>)

Topics: [gpt-6-astra](<https://devfeed.tech/topics/gpt-6-astra.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-2-235](<https://devfeed.tech/tags/ai-2-235.md>), [comparison](<https://devfeed.tech/tags/comparison.md>), [cost](<https://devfeed.tech/tags/cost.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [generative-ai-1-981](<https://devfeed.tech/tags/generative-ai-1-981.md>), [gpt-6-astra](<https://devfeed.tech/tags/gpt-6-astra.md>), [gpt-6-astra-9](<https://devfeed.tech/tags/gpt-6-astra-9.md>), [images](<https://devfeed.tech/tags/images.md>), [llms](<https://devfeed.tech/tags/llms.md>), [llms-1-947](<https://devfeed.tech/tags/llms-1-947.md>), [model](<https://devfeed.tech/tags/model.md>), [openai](<https://devfeed.tech/tags/openai.md>), [openai-463](<https://devfeed.tech/tags/openai-463.md>), [pelican-riding-a-bicycle](<https://devfeed.tech/tags/pelican-riding-a-bicycle.md>), [pelican-riding-a-bicycle-142](<https://devfeed.tech/tags/pelican-riding-a-bicycle-142.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>)

### AI overview

The article compares GPT-6 Astra with GPT-5.6 Sol, Terra, and Luna by generating SVG pelicans riding bicycles at different reasoning levels. The author finds Astra's images generally better, while noting that lower reasoning levels can omit pelican legs and that Astra may cost more but use fewer tokens.

### Source excerpt

I got access to GPT-6 Astra this afternoon, so naturally I used it to generate SVGs of pelicans riding bicycles - at low, medium, high, xhigh and max reasoning levels (Astra doesn't support reasoning=none). Then I rendered those pelicans in a comparison grid with GPT-5.6 Sol, Terra, and Luna, and beyond being fun the result was surprisingly useful. See the grid for full quality images. Here's the transcript that created the GPT-6 Nova pelicans. There are a few interesting things that stand out from this grid. The Astra pelicans are much better. The very best GPT-5.6-Sol pelican (I liked xhigh better than max) is still pretty clearly a bunch of abstract shapes. Every single one of the Astra pelicans, from low to xhigh, looks better than that. The Astra max one is really good. Astra below max still doesn't reliably get the pelican legs on both sides of the frame. In terms of cost, Astra may be around twice the price of Sol ($10/million input, $50/million output, compared to $5/$30 for Sol), but it uses significantly less tokens at each of the levels, making the prices at the different levels closer than they might otherwise be. Astra low produces a better pelican than ANY of the GPT-5.6 Sol models at any level, for 9.55 cents. Spending 10 cents on any other model gets a much worse result. Look at the input token counts: Astra and Luna both used 16 input tokens, Sol and Terra used 26. That's interesting. I wonder if Astra and Luna are more related to each other than OpenAI let on? You are only seeing the long-form articles from my blog. Subscribe to /atom/everything/ to get all of my posts, or take a look at my other subscription options.