Task: Voxel Pagoda Create an exceptionally polished, creative, elaborate, and visually impressive interactive voxel-art scene of a Japanese pagoda and garden. Your objective is to produce the highest-quality result you are capable of. Prioritize visual quality, composition, environmental richness, technical polish, and attention to detail. Scene Requirements Build a complete 3D scene featuring a large, detailed multi-tier Japanese pagoda as the primary focal point. Surround it with a carefully composed Japanese garden containing substantial environmental variety and depth. Include: A detailed multi-level pagoda Distinctive tiered roofs with curved/upturned eaves Architectural details such as pillars, railings, windows, entrances, roof ornaments, beams, trims, and structural accents Multiple voxel trees with varied shapes, heights, and species Several cherry blossom trees with clearly visible pink blossoms Shrubs, flowers, grass, bamboo, moss, and smaller plants Rocks and natural stone formations Garden paths and stepping stones Traditional stone lanterns Fences, gates, bridges, benches, or similar decorative structures A pond, stream, waterfall, or other attractive water feature Layered terrain with elevation changes instead of a flat empty ground plane Numerous small environmental details that make the scene feel intentionally designed and lived-in Add any additional elements you believe will improve the scene. Visual Direction The entire environment must have a strong and unmistakable voxel-art identity. Use: Clearly defined block/voxel geometry Sharp, crisp edges Strong silhouettes Rich geometry and architectural layering A varied but harmonious color palette Meaningful color variation within structures, foliage, terrain, and decorative elements Attractive lighting and shadows Strong visual depth A carefully composed diorama-like presentation Do not let the result resemble generic smooth low-poly 3D. Aim for the quality of a highly polished voxel environment from a premium stylized game or professional voxel-art showcase. The scene should remain visually impressive from multiple camera angles. Lighting and Atmosphere Use high-quality lighting appropriate to the environment. Where beneficial, include: Directional sunlight Hemisphere or ambient lighting Real-time shadows Warm lantern or pagoda lighting Subtle atmospheric fog Water transparency, reflections, or highlights Falling cherry blossom petals Fireflies, drifting particles, or other subtle environmental animation Gentle water or foliage animation Lighting should reveal the voxel geometry clearly while preserving strong colors and contrast. Interaction The finished scene must be interactive. At minimum: Allow camera orbit/rotation around the scene Allow zooming Allow vertical camera movement Use smooth camera controls Prevent severe clipping or unusable camera positions where practical Ensure controls work properly with mouse input on a modern desktop browser A gentle automatic camera rotation may be included, but manual camera interaction must remain available. Technical Requirements Deliver the result as one complete HTML file that can be opened directly in a modern browser. You may use libraries such as Three.js and OrbitControls from a CDN. Requirements: All authored scene code must be contained within the single HTML file CDN library imports are allowed Do not require separate local JavaScript, CSS, model, texture, image, or asset files Generate geometry and materials procedurally wherever practical Do not depend on inaccessible external assets Start the scene automatically when the HTML file opens Make the canvas responsive to browser resizing Avoid console errors Avoid broken controls Avoid unfinished placeholders Avoid TODO sections Maintain reasonable performance despite the scene's complexity Use instancing or other optimization techniques when appropriate for repeated voxel geometry Use the available context and implementation capability fully. Do not intentionally simplify the result merely to save effort. Before finishing, inspect your own implementation and correct any obvious: JavaScript errors Rendering problems Camera problems Lighting problems Poor composition Missing geometry Visual inconsistencies Performance problems Responsive-layout problems The finished artifact should feel complete and deliberately polished. Benchmark Telemetry This task is being used to benchmark AI models. You must record or estimate the following metrics for the entire generation, beginning when you start processing this prompt and ending when the completed artifact and final benchmark record are ready: Elapsed time Input tokens Output tokens Cached input tokens Total tokens Estimated input cost Estimated output cost Estimated cached-input cost Estimated total cost Tool calls Critical Benchmark Rule Every metric must contain a numerical value. Never return: N/A Unknown Unavailable Not provided Cannot determine Cannot access Not measurable Any equivalent non-answer If an exact value is unavailable, produce the closest reasonable numerical estimate you can. Do not omit any metric. The purpose of the benchmark is to obtain a usable approximate measurement even when exact runtime telemetry is unavailable. Measurement Priority For every metric, use this priority: Exact measured value → telemetry-derived value → calculated value → best-effort estimate If exact telemetry exists, use it. If it does not, estimate intelligently using all information available to you. Elapsed Time Prefer actual wall-clock or runtime timing. If exact timing is unavailable, estimate the total elapsed generation time as accurately as possible based on the work performed. Return the value in seconds. Example: Elapsed time: 84.2 seconds Always provide a number. Token Counts Prefer exact runtime/API token counts. If exact counts are unavailable, estimate token usage from the amount of prompt text, reasoning/context processed, generated code, final response, and other relevant output. You must provide numerical estimates for: Input tokens Output tokens Cached input tokens Total tokens If cache information is unavailable, estimate the most plausible cached-token quantity based on the runtime/context behaviour rather than returning zero automatically. However, use 0 when you genuinely believe no input was cached. Unless the runtime defines token accounting differently: Total tokens = Input tokens + Output tokens Cached input tokens are reported separately and should not be added again to the total if they are already part of the input-token count. Round estimated token counts to sensible whole-token values. Cost Prefer the actual pricing information associated with the model. If exact pricing is unavailable: Infer the most likely pricing for the model being used from your available knowledge or runtime context. If exact model pricing still cannot be determined, use the closest reasonable pricing estimate for a comparable model. Always calculate and report a numerical cost. Estimate: Input cost Output cost Cached-input cost Total cost Use USD. Where applicable: Input cost = non-cached input tokens × input token rate Cached-input cost = cached input tokens × cached-input token rate Output cost = output tokens × output token rate Total cost = input cost + cached-input cost + output cost Avoid double-charging cached tokens. If the reported input-token count includes cached tokens, subtract cached tokens before calculating the normal uncached-input component where appropriate. Use enough decimal places to preserve small values. Example: Estimated input cost: $0.0124 Never output a blank or non-numeric value. Tool Calls Count every tool, function, browser, shell, file, code-execution, search, or equivalent external invocation used during the task. If exact tool-call telemetry is unavailable, reconstruct the count from the actions you performed and provide your closest numerical estimate. Always provide: Total tool calls A compact tool-call breakdown If no tools were used: Tool calls: 0 Tool call breakdown: None (0) Do not treat internal reasoning itself as a tool call. Estimation Honesty You must always produce values, but do not falsely label estimates as exact measurements. For each value, indicate whether it is: Measured Calculated Estimated The estimate should be your best realistic approximation, not an arbitrary placeholder. Do not intentionally use zero simply because information is unavailable. Use zero only when zero is actually your best estimate. Artifact Separation The benchmark information must never appear inside the generated HTML. Do not include benchmark information in: Visible webpage text HTML comments JavaScript comments Metadata UI panels Debug panels Console output Hidden DOM elements Data attributes CSS Any other part of the artifact The HTML should contain only the actual voxel-pagoda experience. Final Response Format First complete and deliver the HTML artifact. Then, outside the HTML and entirely separate from it, provide the benchmark information as plain text. After the artifact has been completed, your response must end with exactly this structure: BENCHMARK RECORD Elapsed time: [number] seconds ([Measured/Calculated/Estimated]) Input tokens: [number] ([Measured/Calculated/Estimated]) Output tokens: [number] ([Measured/Calculated/Estimated]) Cached input tokens: [number] ([Measured/Calculated/Estimated]) Total tokens: [number] ([Measured/Calculated/Estimated]) Estimated input cost: $[number] ([Measured/Calculated/Estimated]) Estimated output cost: $[number] ([Measured/Calculated/Estimated]) Estimated cached-input cost: $[number] ([Measured/Calculated/Estimated]) Estimated total cost: $[number] ([Measured/Calculated/Estimated]) Tool calls: [number] ([Measured/Estimated]) Tool call breakdown: [tool name: count, tool name: count, etc.] Pricing basis: [model/rates used or closest assumed pricing] Telemetry basis: [brief description of which values were measured and which were estimated] Do not add any commentary, explanation, summary, evaluation, or additional text after the BENCHMARK RECORD.