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mflux-teacache

PyPIInfrastructure

No liveness check has reached it yet; it is registered on GitHub and PyPI and has been in the index since 9 Oct 2026. How this is checked

mflux-teacache is an open-source plugin that adds TeaCache step skipping to the mflux command-line diffusion workflow. It is designed for local image-generation inference on Apple Silicon and is distributed through PyPI.

Inferred · not functionally tested

Open SourceApache-2.0CLISelf-hosted
Visit PyPI

Overview

5 features

Purpose: Reducing local diffusion inference time by skipping redundant computation steps in mflux.

Inferred · not functionally tested

Audience: developers and Apple Silicon users running local diffusion models

Inferred · not functionally tested

Functions: Unknown

Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)

Recorded constraints: pricing: open_source · license: Apache-2.0 · platforms: CLI · deployment: cli, self_hosted

Constraint provenance is unknown; confirm requirements with the publisher.

Record sources: pypi.org · github.com. These links do not verify the individual claims.

In the Inference & model serving space, mflux-teacache takes a focused approach. Inferred · not functionally tested: It focuses on reducing local diffusion inference time by skipping redundant computation steps in mflux. Inferred · not functionally tested: It is built as an open-source project for developers and Apple Silicon users running local diffusion models. Basis unknown · not verified: mflux-teacache is open source under the Apache-2.0 license. Basis unknown · not verified: It runs on the command line, and it can be self-hosted.

Behind mflux-teacache is mflux-community, and it first shipped in 2026. The project is developed in the open on GitHub with 7 commits in the last 90 days. Inferred · not functionally tested: Key capabilities include teaCache step skipping, mflux CLI integration, and local inference.

Summary written by a language model from the project’s public pages.

Tasks: Inferred · not functionally tested

  • TeaCache step skipping
  • mflux CLI integration
  • Local inference
  • Apple Silicon support
  • Diffusion acceleration

Topics: Inferred · not functionally tested

Tags
teacachediffusion-accelerationapple-siliconmflux-plugin
AI capabilities
Image
Inference: Local

JSON profile · Text profile · Access guide

Built with & integrations

AI providers
local_oss
Written with
Unspecified agent
Runs on
CLISelf-hosted
Written with — evidence
Unspecified agent
AGENTS.md

Trust & compliance

License
Apache-2.0
Public signals
HTTPSOpen SourceFree tierGitHubActive maintenance

Indexing history

1

What PulseGate has recorded for this listing

  1. Indexed9 Oct · 11:57 UTC
    mflux-teacache seen via PyPI Bulk Enumerator
    Source: PyPI Bulk Enumerator · Open

Frequently asked questions about mflux-teacache

What does mflux-teacache do?
Inferred · not functionally tested: Mflux-teacache focuses on reducing local diffusion inference time by skipping redundant computation steps in mflux. It is catalogued under Inference & model serving on PulseGate.
Who should use mflux-teacache?
Inferred · not functionally tested: mflux-teacache is an open-source project built for developers and Apple Silicon users running local diffusion models.
Is mflux-teacache free?
Basis unknown · not verified: Yes — mflux-teacache is open source under the Apache-2.0 license and free to use.
What platforms does mflux-teacache run on?
Basis unknown · not verified: mflux-teacache runs on the command line. It can also be self-hosted.
Is mflux-teacache still maintained?
The GitHub repository shows 7 commits in the last 90 days.
What projects are similar to mflux-teacache?
Similar projects tracked by PulseGate include TokenRouter, GPUYard, and GPUniq.TokenRouterGPUYardGPUniq
Who develops mflux-teacache?
mflux-teacache is developed by mflux-community.
When did mflux-teacache launch?
mflux-teacache first shipped in 2026.

Also in Inference & model serving

Same category — not a similarity match