AI Model Profile

Stable Diffusion 3.5 Large Turbo

Stable Diffusion 3.5 Large Turbo is Stability AI's distilled SD3.5 Large variant for faster image generation with fewer steps.

Before you buy

Best for: Fast local or hosted image generation where SD3.5 prompt adherence matters.

Price: C$0 weight download; license restrictions and compute costs apply

Included: Stable Diffusion 3.5 Large Turbo is Stability AI's distilled SD3.5 Large variant for faster image generation with fewer steps.

Main limits: Verify Stability Community License terms before commercial deployment. Hardware depends on precision, runtime, and optimization path. Availability, pricing, and real-world quality should be rechecked against official docs and a task-specific evaluation before production use.

What Kingy showed: Related coverage: Local AI Models: The Definitive Guide to Planning, Hardware, Setup, Installation, Model Selection, Testing, and Real-World Use. This review does not treat that article as a new test of this exact model, plan or current release.

Buying details checked 2026-10-23 with region and currency stated above. Historical demonstrations and the broader fact ledger keep their own dates.

See the demonstration and disclosure · Compare these workflows

Family
Stable Diffusion
Release date
Unknown
Status
Current
Context window
Unknown
Output limit
Unknown
API
yes
Open weights
yes
Local/self-hosted
yes
Pricing
Open weights plus optional API/hosted inference costs.
Evidence state
Recheck due

Benchmark Caveat

Benchmarks and provider capability notes are directional, not universal rankings. Results can shift with prompts, tool use, latency targets, pricing tier, safety filters, context length, and the workload mix a real team runs.

See the linked official model, docs, model-card, or pricing source for provider-published capability notes.

Best for

Fast local or hosted image generation where SD3.5 prompt adherence matters.

Skip if

Skip if absolute image quality matters more than fewer-step speed.

Strengths

Stability AI describes Large Turbo as a distilled version of SD3.5 Large that generates high-quality images in fewer steps.

Weaknesses

Availability, pricing, and real-world quality should be rechecked against official docs and a task-specific evaluation before production use.

Kingy AI take

Use this as a source-backed shortlist candidate, not a universal ranking. Re-check official provider docs and run a task-specific trial before production adoption.

Kingy AI Product Facts

Stable Diffusion 3.5 Large Turbo

Current statusUnknown

Company
Not yet reviewed
Primary job
Not yet reviewed
Audience
Not yet reviewed
Evidence
Source-backed; coverage expanding
Latest source check
October 23, 2026
See all tracked product factsPricing, platforms, dependencies, data claims, regions, and timeline

Sources and checks

Coverage
1 of 88 tracked fields currently verified
Sources
1

Source-check dates apply to the tracked facts. Editorial updates elsewhere on this page may have a different date.

Plans and pricing units

Not yet structured in this Kingy record.

Where it runs

Availability
Not yet reviewed

Stack and integrations

Model / provider dependencies
Not yet reviewed
Integrations
Not yet reviewed

Data and regions

Vendor data-use claim
Not yet reviewed
Vendor retention claim
Not yet reviewed
Regions
Not yet reviewed

Launch and latest material update

Launch
Not yet reviewed
Latest material update
Not yet reviewed
Technical evidence and revision history
Embed “Facts tracked by Kingy”

This label is not a security certification, audit, or product endorsement. It reports the facts Kingy currently supports and when they were last checked.

Full Model Notes

Who should consider it

Fast local or hosted image generation where SD3.5 prompt adherence matters. Stable Diffusion 3.5 Large Turbo is Stability AI's distilled SD3.5 Large variant for faster image generation with fewer steps.

Plan, price and billing scope

C$0 weight download; license restrictions and compute costs apply. Stable Diffusion 3.5 Large Turbo is Stability AI's distilled SD3.5 Large variant for faster image generation with fewer steps. Prices use the currency and billing term stated here. Where a numeric rate, region or current entitlement could not be verified, it remains explicit; no checkout was completed.

Limits that affect the decision

Verify Stability Community License terms before commercial deployment. Hardware depends on precision, runtime, and optimization path. Availability, pricing, and real-world quality should be rechecked against official docs and a task-specific evaluation before production use.

What the existing evidence shows

Related coverage: Local AI Models: The Definitive Guide to Planning, Hardware, Setup, Installation, Model Selection, Testing, and Real-World Use. This review does not treat that article as a new test of this exact model, plan or current release. Related workflow reading; not a demonstration of this exact product. Read the related article.

Sources and buying-review date

Buying review completed October 23, 2026. This is a source-based buying assessment. No paid product test, new generation, checkout or performance benchmark was performed. Vendor descriptions and historical examples remain distinct from independently measured results. The date does not renew the broader canonical fact ledger.

Check the official offer · Compare related options

Earlier profile, sources and dates

This older record retains its original scope. Current buying qualifications above take precedence where terms have changed.

Stable Diffusion 3.5 Large Turbo is Stability AI’s distilled SD3.5 Large variant for faster image generation with fewer steps.

Creative notes

Use a small creative test set before standardizing outputs for brand, media, or customer-facing work.

API pricing notes

Check the official pricing page before budget decisions; Kingy does not freeze token, credit, or subscription prices in model cards.

License notes

Verify Stability Community License terms before commercial deployment.

Hardware requirements

Hardware depends on precision, runtime, and optimization path.