EcoCompute Should-I-Quantize Estimator

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

• Connection: Runs in the cloud
• Transport: Streamable HTTP
• Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

You need

• Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp

claude mcp add --transport http ecocompute-estimator https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp

{
  "mcpServers": {
    "ecocompute-estimator": {
      "url": "https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp"
    }
  }
}

{
  "servers": {
    "ecocompute-estimator": {
      "type": "http",
      "url": "https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp"
    }
  }
}

https://ecocompute-estimator.zhanghongping1982.workers.dev/mcp

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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.

• 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 basis (measured/interpolated/estimated), confidence and evidence boundaries.

• 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 coverage, and to answer 'is there data for my GPU?' honestly.

• 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.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

• ✓ Pass

  Maker matches the repo

  The registry name was verified with the GitHub account hongping-zh, which owns the repo

• … Not checked yet

  Still maintained

  We have not read this repo from GitHub yet

• … Not checked yet

  Has a licence

  We have not read this repo from GitHub yet

• ✓ Pass

  Endpoint responds

  Responded in 204 ms (HTTP 200)

• – Not applicable

  Sign-in with OAuth

  No sign-in needed

• ✓ Pass

  No hidden instructions in tool descriptions

  Read 4 tool descriptions and found no hidden instructions to the AI

Compared with others in Search & AI memoryi

• More stars than 0% of the other 5688 servers in this category
• Published to the registry more recently than 72% of the other 5688 servers in this category
• Basic checks equal to or better than 100% of the other 5688 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

README from the maker