GPT-6 Astra in Codex CLI 0.156.1
skills off
Web model exported by this site from the scene.blend the agent saved during the run. The model is not a deliverable produced by the agent. The render and original scene are separate downloads below.
Wall time 29m 10sCost $7.78 estimated
Review
No verdict yet.
The full review
OK. Finished on its own after 29.2 min.
Scores
AI judge
Not scored
No rubric for this prompt
Visitor votes and reviewer grades are not available yet.
- AI judge
- AI judge: the test runner (model claude-opus-5-5), scoring by visual review of the 1600 px render against the pre-registered rubric. No AI-judge score exists for this result: there is no rubric for this prompt, so no score is shown and none is made up.
- Visitors
- Public voting with a blind reveal is coming: you score the output first, then see the other scores.
- Reviewer
- The reviewer's own grade appears here once it is added.
Scores compare results for the same prompt only. AI-judge boards rank runs within one prompt, equal totals sharing a rank; scores from different prompts are never averaged.
Downloads
Files actually published for this run. Original output, site-made previews and post-run conversions are labelled separately.
The exact prompt
as run, 614 characters. Every result for this prompt
Make me a donut in Blender. Blender 5.2 is already running on this machine with the MCP for Blender add-on connected: build the scene in that Blender through the blender MCP tools (its window is on a virtual screen and there is no GPU, so render on the CPU). When you are finished, set up a camera and render the final image at 1920x1080, saving it as render.png in the current directory (Blender's working directory is this same folder), and save the Blender file as scene.blend here too. You may take viewport screenshots and look at your own renders to check your work, and iterate on your own before finishing.
How it was made
Step by step
The prompt, every agent turn and tool call (tool name and a one-line summary; inputs and outputs are not shown), then the final message. The full machine-format transcript is published as a scrubbed download.
Show all 103 steps
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Download the full transcript Codex CLI rollout JSONL, 803 KB. Scrubbed: anything that looks like a key, token, e-mail address or phone number is replaced, and account details and the test machine's file paths are removed.
Cost breakdown
Headline cost $7.78, estimated from the token counts at list price.
| Tokens by type | Tokens | $ per 1M | Cost |
|---|---|---|---|
| Input (uncached) | 192 | $10.00 | $0.0019 |
| Cache write | 99,161 | $10.00 | $0.9916 |
| Cache read | 4,700,488 | $1.00 | $4.7005 |
| Output | 41,724 | $50.00 | $2.0862 |
| of which reasoning | 23,509 | billed as output |
- Total computed from tokens
- $7.7802
- Total reported by the harness
- none
Computed from harness-reported token counts x list prices. Cache writes priced at the input rate (the price table has no separate cache-write price).
Prices: Project price table (vendor list prices), 2026-09-22.
Run notes
- frozen prompt (reconstructed): recovery/prompts_recovered/blender_donut.assembled_candidate.txt: verbatim ask + recorded harness suffix
- plain CODEX_HOME copy (config.toml only, run work/ trusted; no AGENTS.md/skills/state)
- W6: Blender 5.2.2 GUI on a private Xvfb display inside the sandbox (filesystem socket in the sandbox's own /tmp only, per-run cookie), software OpenGL (llvmpipe), render threads 2; working directory = the run's work dir
- Run on a GitHub Codespace (codespaces lane of box-fleet); model calls reached the providers through a credential relay on the home machine (no keys in the codespace).
- Mode: interactive TUI in tmux (160x48), inside bubblewrap sandbox
- Isolation audit: contamination