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To find out whether ten LLMs can produce a working Blender 5.0 script, give each the same bounded task, run every unedited answer in the same Blender build and scene state, and score the results against checks you set in advance. A script that runs without an error is only a partial success: it must also create the requested result.
This is a reproducible test plan, not a report of completed model runs. No ten-model results or performance ranking are established here. Blender 5.0 is the deliberate target: it was initially released on November 18, 2025, and Blender 5.2 LTS followed on July 14, 2026. Record the exact 5.0 build you use rather than presenting it as Blender’s newest version. Blender 5.0 release details; Blender 5.2 LTS release details.
Why specify Blender 5.0?
Blender’s Python API changes between releases, so a script that worked with an earlier version may need adaptation. The Blender 5.0 API notes describe compatibility-relevant changes to property storage access, bundled Python modules, animation APIs, and GPU APIs. Ask for code that targets Blender 5.0 and uses documented public APIs; do not assume code written for another release will behave the same way. Read the Blender 5.0 Python API release notes.
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#1 Best Overall
Choose one task and define what success means
Use the same task for all ten systems. A small scene or procedural object is a practical choice because you can inspect both whether the script ran and what it produced. Avoid asking for a broad “useful Blender script”: answers could differ so much that the comparison becomes subjective.
Write the rubric before prompting
Turn the task into observable checks. For example, if your task asks for a simple scene, specify the required objects, their key settings, and the visible result you expect. Then score each output on the same criteria:
Rank #2
- Execution: Did the untouched script run without an exception?
- Required result: Did it create the specified objects and settings?
- Scene quality: Did the resulting scene meet the visual or structural checks you wrote down?
- Correction effort: How much editing was needed to reach the required result?
- API fit: Did it use documented APIs appropriate to Blender 5.0?
Keep these dimensions separate. Readability, correctness, and execution speed are not interchangeable, and combining them into one score can conceal why an answer succeeded or failed.
Keep the ten prompts and runs comparable
- Record the test environment. Note the exact Blender 5.0 version and build, operating system, and project state. Record each model or product name and the date you accessed it, along with relevant settings such as code mode, tool access, or reasoning options.
- Use one prompt. Give every system the same task, constraints, and requested output format. Do not quietly add clarification to one system that the others did not receive.
- Save every answer verbatim. Preserve the complete original outputs before editing. If an answer needs correction, keep both the original and corrected version so the initial result remains measurable.
- Start each run from a comparable state. Use a clean project or reset the scene consistently before running each script. This reduces the chance that objects left by a previous run affect the next result.
- Inspect before execution. Review generated code and use a disposable project if you are concerned about data loss or security. This is a prudent precaution for running generated scripts, not evidence that any particular model output is harmful.
- Run, inspect, and log. Record whether the script executes unedited, what it creates, whether it meets the rubric, and every manual intervention. Save the error traceback when it fails.
Blender 5.0’s API reference documents bpy.ops.script.python_file_run(filepath='') as the “Run Python file” operator. That confirms an official operator for running a Python file, but it does not establish that every interface workflow or button sequence is identical across builds. Blender 5.0 Script Operators reference.
Classify failures instead of counting only wins
A traceback and the resulting scene help distinguish different failure modes. Record what happened rather than labeling every unsuccessful result simply “bad code.”
- Syntax error: Blender cannot parse the script, so it stops before completing the instructions.
- API incompatibility: The script calls an API that is unavailable or behaves differently in the requested Blender version. Compare the relevant call with the Blender 5.0 API notes.
- Context problem: An operation depends on Blender’s current editor, selection, mode, or other context and fails in the state where it was run.
- Incorrect output: The script finishes, but the scene does not satisfy the task’s object, setting, or visual checks.
- Manual repair: The script reaches the target only after edits. Record those changes and do not count the repaired version as an unedited success.
Report results so readers can reproduce the comparison
For each system, publish the model or product name, access date, relevant generation settings, whether its original output ran without edits, whether the result passed each rubric check, and the corrections required. Include the denominator and describe failures as well as successes. Preserve enough prompt and output detail for another reader to repeat the test, subject to any applicable publication or privacy constraints.
Rank #4
Do not claim a model is “best” based on a single blended score unless you explain how the score was calculated and what it weights. A ranking also needs actual recorded runs; Blender’s release statistics do not measure LLM script performance. Blender’s 5.0 overview reports 588 bugs fixed in the release, a figure about Blender’s release, not about generated code. Blender 5.0 overview.
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