Zed

Zed can send inference to hosted models or local Ollama/LM Studio servers. Local use makes device electricity measurable, but Zed publishes no comparison between that path and hosted inference. Choose a compact model where suitable and measure a complete editing task—including context and retries—before claiming an energy benefit.

No per-task electricity, water, or emissions data, serving-region breakdown, or lifecycle assessment was found for the harness.

• Zed local model configuration ↗

Zed’s own Edit Prediction training collection is opt-in and restricted to open-source projects, and its Zeta2 page describes the dataset approach. That is meaningful evidence for Zed’s own model, not a blanket endorsement of BYO providers or external agents. Prefer the Zed model if those controls fit, and audit each outside model separately.

The provider and exact model vary by configuration; no complete rights ledger can be inferred from the harness license or provider list.

• Zed AI improvement and opt-in training data ↗
• Zed Zeta2 training data and model disclosure ↗

The product gives clear controls for its hosted model path, though Anthropic-designated models may retain prompts for safety and BYO/external agents follow their own terms. Choose an eligible no-retention model or local provider if provider-side retention is unacceptable.

Plan, selected model/provider, enabled features, and deployment mode can change this assessment.

• Official privacy or data-processing disclosure ↗
• Official privacy or data-processing disclosure ↗

Zed publishes its editor code under GPL-3.0 and its collaboration server under AGPL-3.0, making those components inspectable under their respective licenses. Its hosted AI features and selected models are separate services. Inspect the relevant component license before deciding how to modify or deploy it.

This score covers the harness/editor source only; hosted services, models, data, or enterprise features may remain proprietary.

• Zed official privacy or open-source documentation ↗
• Official privacy or data-processing disclosure ↗

Zed’s public source and opt-in training rules make some product development choices inspectable, but do not reveal contributor compensation or model-provider labor practices. The separate Zeta training dataset is not a workforce report. Support the project if you rely on it and review labor practices for the chosen external model.

Current worker pay, working conditions, subcontracting, safety provisions, and grievance outcomes are not established for this product’s full service chain.

• Zed ↗
• Zed AI improvement and opt-in training data ↗

The product sources reviewed do not identify Zed as used in a named defense, weapons, or surveillance deployment. Where this harness lets users choose models or hosts, the underlying provider’s contracts and controls can change the picture; no relationship for this product is established here. Check the selected model, host, and company contract record before treating the tool as suitable for sensitive work.

No public evidence in the reviewed material names this harness in a defense workload; absence in this review does not establish absence of indirect use.

• Zed local model configuration ↗

Zed Industries is not a named target in the checked lists, but BDS uses selective campaigns, so absence cannot establish a clean record. Check the model and host this tool connects to as well as the company providing the tool.

This review covers the named targets in the BNC consumer/pressure guide and No Tech campaign, not every BDS campaign, local group, investment or supplier. Lists and ownership can change. A company’s absence from these lists is not an endorsement or proof that it has no relevant relationships.

• BNC: live guide to consumer boycott and pressure targets ↗
• BNC: No Tech for Oppression, Apartheid or Genocide campaign ↗