You are participating in Blender-Bench, a public benchmark where AI models complete the same Blender task.

Your result will be compared head-to-head with another model. Anyone on the internet can vote, based only on the published visual outputs they can inspect: the interactive 3D scene and rendered presentation.

Complete the request as well as you can. The benchmark does not prescribe a workflow or visual style; use whichever Blender techniques you consider appropriate. Make the important requirements evident in the published result, save a complete scene, and present the work clearly in every requested output.

The final published capture is rendered by the benchmark from your saved scene using Cycles at 1536 x 1536, 64 samples, denoising enabled, and GPU acceleration when available with a CPU fallback. The saved scene is also exported to GLB with geometry, materials, the contestant camera, and supported lights for interactive inspection. Preview and validate your materials, lighting, color management, and camera composition in Cycles, and do not rely on EEVEE-only effects for the final appearance.

## Harness Instructions

You are operating Blender through the provided tools. The scene starts empty. Build what the user's prompt asks for in the current scene. Work step by step and verify your own work. Before you finish, set up a camera and lighting to frame a single, well-composed presentation image of your result — position and aim the camera, and add or adjust lights so the subject reads clearly. The final benchmark capture overrides the scene render settings and renders in Cycles at 1536x1536, 64 samples, with denoising and GPU acceleration (CPU fallback). Preview and validate materials, lighting, color management, and composition in Cycles; do not rely on EEVEE-only effects. The saved scene is also exported to GLB with geometry, materials, your camera, and supported lights for interactive inspection. When you are finished, reply with the single word DONE and no tool calls.


type: user

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## Task

Complete the following Blender task:

<task>

A desk-mounted robotic arm with at least four articulated joints, posed mid-reach toward a small object on the desk — but not an industrial catalog part. This arm is generatively designed: its metal frame has the parametric, "AI-optimized" look of topology-optimized engineering — organic load-bearing branches, smooth bone-like transitions, lattice or voronoi-style cutouts where material was removed because the algorithm decided nothing needed to be there. Every strut should look grown to carry its exact load, not extruded.

Over that frame, a second material layer: woven technical fabric. Tensioned textile sleeves and panels — visible weave pattern, carbon-fiber or ballistic-cloth character — wrap sections of the segments over the optimized metal skeleton, so the arm reads as engineered musculature over engineered bone. The interplay of the two materials (taut woven fiber against machined/printed alloy) is the material centerpiece.

The manipulator: a three-clawed gripper at the wrist — three fingers in radial symmetry, each with the same optimized-lattice construction in miniature, posed partly open toward the target object. The gripper connects to the forearm through corrugated hose: flexible ribbed tubing gathered at the wrist, running back along the arm as its visible service umbilical (power, data, pneumatics), routed and clipped like it was engineered, not draped.

The mechanics must still look like they could actually work: visible rotation axes at every joint, with actuators, cable runs, or tendon-like elements explaining how each segment moves; segments tapering plausibly from a heavy base to the fine three-claw head. The pose must be believable for the joint layout: no segment intersecting another, no joint bent in a way its geometry couldn't allow.

</task>