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EcoCompute Should-I-Quantize Estimator

by FastDrop

MCP Verified 2 hours ago Registry import free

Energy impact of LLM quantization, calibrated to measured GPU data. Every answer states its basis.

Energy impact of LLM quantization, calibrated to measured GPU data. Every answer states its basis. Official MCP Registry: io.github.hongping-zh/ecocompute-estimator@1.0.0. Remote endpoint: https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp

Problem it solves

Discoverable MCP server listed in the official MCP Registry.

How it's different

Remote MCP endpoint ingested from the official registry and probed by FastDrop.

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as io.github.hongping-zh/ecocompute-estimator and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 24 Oct 2026. Not supplied by the maker.

  • estimate_quantization_energy

    Estimate the task-level energy change (ΔE% vs FP16) of weight-only quantization (NF4 or INT8) for a model of a given size on a GPU architecture class, from measured-anchored curves. The answer carries

  • get_quantization_crossover

    Get the model-size crossover for NF4/INT8 per architecture: below it quantization costs energy, above it saves. Crossovers belong to a card + software stack, not an architecture — the answer says so.

  • list_data_coverage

    List what is actually measured (GPU architecture × precision × size range, NVML direct), what is borrowed/estimated, and where the gaps are. Use this before trusting an estimate at the edges of covera

  • search_measurements

    Search the measured anchors by model name, GPU name, architecture or size. Returns ΔE% vs FP16 per anchor with run counts — the raw evidence behind the curves.

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