AI Tool Profile

LM Studio

LM Studio is a desktop app for discovering, downloading, running, and serving local language models.

AI-generated editorial image of an AI tool scorecard interface with source, pricing, demo, API, and limitation checks

Verification & Sources

Evidence state
Recheck due
Source links
1
Freshness
Needs recheck: checked June 24, 2026
Last updated
June 24, 2026
What this evidence state means
Definition
The claim was previously checked, but its review window expired or a material change may have invalidated it.
Required provenance
The prior evidence and check date are retained, together with the expiry or change signal that triggered recheck.
Owner
Kingy freshness queue owner and assigned editorial reviewer
Freshness rule
This is already outside its freshness rule. It must not be presented as current until reviewed against current evidence.
Disputes and corrections
Use “Suggest a correction” on the record. Kingy editorial reviews the cited evidence, records material corrections, and changes or removes the state when it is not supported.

Key source checks

Suggest a correction

Form submissions, correction notes, score details, URLs, and analytics events may be stored for editorial review, spam prevention, product improvement, and follow-up. Do not submit secrets, unreleased financials, private customer data, or regulated personal data through these forms.

What It Does

LM Studio is a desktop app for discovering, downloading, running, and serving local language models.

Launch History

AI Local Models

LM Studio 0.4.0 launch

LM Studio introduced version 0.4.0 with server deployment, parallel requests, continuous batching, a new REST API endpoint, and a refreshed UI.

Recheck due Free: Yes API: Yes Open: No
Clear use caseVideo demoBeginner-friendlyDeveloper-friendly
Launch readiness
7.1 / 10
Demo evidence
Not scored yet
Creator-story fit
Not scored yet
Score definitions and rubric

These are launch-record readiness heuristics, not product ratings.

Launch readiness

How complete and reviewable the launch record is, not the quality of the product.

Inputs and weights: Launch date 15%; qualifying source 10%; what launched 10%; demo 15%; category 10%; audience 10%; editorial assessment 10%; traction evidence 10%; creator or audience fit 10%.

Evidence inputs: Reviewed launch metadata, public source links, demo links, taxonomy, audience, editorial notes, and recorded traction signals.

Demo evidence

Whether the record contains useful, reviewable demonstration evidence; it is not a rating of product output quality.

Inputs and weights: Working demo URL 45%; video walkthrough 25%; clear description of what launched 10%; audience 10%; editorial assessment 10%.

Evidence inputs: Demo and video URLs plus the reviewed launch description, audience, and editorial notes.

Creator-story fit

Whether a launch has enough demonstrable evidence and audience relevance for a useful creator story; it does not predict views or guarantee coverage.

Inputs and weights: Demo evidence 25%; visual creator category 15%; audience 15%; editorial assessment 15%; traction evidence 10%; pricing clarity 10%; API or open-weight evidence 10%.

Evidence inputs: Reviewed demo, category, audience, editorial, traction, pricing, API, and open-weight fields.

Scale
0.0–10.0. A present qualifying input receives its published weight; a missing input receives zero. Scores are rounded to one decimal.
Assigned by
Suggested by the deterministic field-completeness helper and assigned or approved by a Kingy editorial reviewer.
Rubric and check date
Rubric version P0-2026-08-10. The record’s “Last verified” date is the score check date. Checked: 2026-06-24.
Confidence and missing data
Confidence depends on source completeness. “Not scored yet” means no reviewed value; “Needs review” means the value or score set failed validation.
Freshness
Recalculate after a material launch, source, demo, pricing, audience, or traction change and during the record freshness review.
Disputes
Use “Suggest a correction” on the record and cite the relevant evidence. Commercial relationships cannot buy or alter a score.

LM Studio introduced version 0.4.0 with server deployment, parallel requests, continuous batching, a new REST API endpoint, and a refreshed UI (lmstudio.ai). Developers, Researchers,…