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Kyle Balmer

FIELD GUIDE · 01

Open Source vs. Open Weights: The Plain-English Guide & Checklist

A practical guide for checking what a model label actually gives you before you download, host, or use it.

A plain-language screening tool that helps readers avoid confusing openness, price, local deployment, and control.

A PRACTICAL SCREENING GUIDE

Separate the labels before you decide

Model labels often collapse four separate questions into one: what you can inspect, what you can modify, what you may use under the license, and where the model can run. Treat “open source,” “open weight,” “local,” and “free” as claims to verify—not interchangeable benefits. Before downloading a model, committing to a hosted service, or planning a deployment, identify exactly what is being provided and what your equipment can realistically handle. This guide gives you a plain-English way to classify the model, check its practical limits, and avoid assuming that downloadable weights automatically mean zero cost, full control, or local operation.

THE CORE DISTINCTION

Start with closed source, open weights, and open source

A closed-source model is primarily something you access as a service. You can ask it to perform work, but you do not receive the trained weights that make the model operate. Think of this as taking a taxi: you choose the destination, but somebody else owns, maintains, and operates the vehicle. Open weights means the trained parameters—the model’s “brain”—are available to download. You may be able to use those weights yourself, host them, or fine-tune them. That is closer to owning a car: you have more control over how you use it, while still taking responsibility for running and maintaining it. Fully open source is a higher bar. It aims to provide the materials needed to understand and recreate the model rather than only its trained weights.

WHAT FULL OPENNESS REQUIRES

Use the kit-car test to assess control

When a model is described as fully open source, look beyond the downloadable files. The strongest version of openness includes the weights and parameters, the code around the model, its architecture, and information about the training process. It may also include training-data information or indicate where the data came from so others can retrain the model. Use the kit-car test. Open weights are like receiving a finished car that you can drive and modify. Fully open source is like receiving the parts, plans, and instructions to assemble the car yourself. If the listing only supplies trained weight files, describe it as open weight rather than assuming the complete model-building process is available.

AVOID THE TWO COMMON ASSUMPTIONS

Keep price, permission, and location separate

Do not let one label answer a different question. “Open source” does not automatically mean free, and “open weight” does not automatically mean local. A model can make its weights available while still carrying license conditions that limit personal, internal, fine-tuning, or commercial use. Read the license for the use you intend—not just the headline label. Likewise, downloadable weights can be hosted on your own infrastructure, rented data-center hardware, or another provider’s service. That is different from running the model on your own computer. Separate the questions: What can I access? What am I allowed to do? What will it cost to run? Where can it realistically run?

THE LOCAL REALITY CHECK

Confirm whether local use is realistic

Local use is a hardware question. Model size, usually expressed through its parameter count, helps determine the hardware required. Very large models may be available to download but remain unrealistic for a normal PC or Mac. Their files can also be extremely large, and running the full model may require specialized hardware or a data center. Some model versions are quantized: their numerical representation is compressed, reducing hardware demands while also reducing resolution in those values. Quantization may make a model more practical to run, but it does not erase the need to check the actual version and its requirements. Treat “can be hosted” and “can run on my equipment” as separate claims.

TURN LABELS INTO A DECISION

Create a one-page model record

When comparing model listings, make a short record before you download anything. Write down the label used by the publisher, then replace it with the evidence you can verify: weights only, or weights plus code, architecture, training-process information, and data-source information. Record the license separately from the technical files. Finally, note the model size, download size, available versions, and the hardware needed for the version you would actually run. This turns an ambiguous marketing label into a decision you can explain: use a closed service, run open weights on rented infrastructure, try a smaller local version, or look for a model with fuller source materials.

Download, hosting, and use checklist

Identify whether you are accessing a closed service or downloading the model’s trained weights.
Check whether the release includes weights, supporting code, model architecture, and training-process information.
Check whether the release provides training-data information or identifies the sources needed to recreate training.
Read the model license and confirm that it permits your intended personal, internal, fine-tuning, or commercial use.
Separate the cost to obtain the model from the cost to host, operate, maintain, or access it.
Record the model’s parameter size and the total download size for the version you plan to use.
Confirm the hardware requirements for that specific version before calling it a local model.
Decide whether your own computer can run the model, whether you need specialised hardware, or whether you need rented data-centre infrastructure.
Check whether a quantised version is available and assess that version’s hardware requirements separately.
Describe the model using the evidence you found: closed source, open weight, or fully open source.

APPLY THE GUIDE

Make your next choice with evidence

Use this checklist on the next model you evaluate. Start with the claim that matters most to your decision—control, permitted use, cost, or local deployment—then verify that claim in the model files, documentation, license, and hardware requirements. If a listing says “open source” but only provides weights, call it open weight. If it is downloadable but needs data-centre hardware, do not treat it as a practical local option. Clear terminology makes it easier to choose the right level of control and infrastructure for the work at hand.

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