FLUX.1 vs Midjourney

Side-by-side — pricing, strengths, tradeoffs, and fit.

FLUX.1

Open-weight text-to-image model from Black Forest Labs with state-of-the-art quality and API access.

Midjourney

Generate high-aesthetic images from text prompts, known for its distinctive artistic quality.

At a glance

Open SourceFree TierEnterprise
◌ Declining·From $0.003/image (API)
Enterprise
● Established·From $10/mo

Overview

One-liner

Open-weight text-to-image model from Black Forest Labs with state-of-the-art quality and API access.

One-liner

Generate high-aesthetic images from text prompts, known for its distinctive artistic quality.

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✕ No

Pricing

Free tier

✓ Available

Open weights (schnell) are free to self-host

Free tier

✕ None

Starts at

$0.003/image (API)

Starts at

$10/mo

Model

Usage-based

Model

Per seat

Enterprise

✓ Available

Enterprise

✓ Available

Best for

✓ Best for

Developers wanting open weights and self-hostingRun locally with full control and no per-image fees (schnell)
API image generation with cost controlHosted via Replicate/fal at competitive per-image pricing

✓ Best for

Designers and marketers who want striking visuals fastTop aesthetic quality with minimal prompt engineering
Concept art, mood boards, and editorial imageryStrong stylization and artistic coherence

Not ideal for

✕ Not for

Non-technical users wanting a polished appNo consumer app — access is via API or self-hosted UIs
Commercial use of the dev weights without a licenseFLUX.1 [dev] is non-commercial; use schnell or Pro/API

✕ Not for

Free/zero-budget projectsNo usable free tier — a paid subscription is required
Pixel-precise structural controlLacks the ControlNet/inpainting precision of open Stable Diffusion stacks

Strengths

↑ Strengths

State-of-the-art quality for an open model
Self-hostable open weights
Broad ecosystem and API availability

↑ Strengths

Best-in-class aesthetic quality out of the box
Excellent prompt adherence and style control
Fast iteration with variations and upscaling

Weaknesses

↓ Weaknesses

Lack of official fine-tuning code and uncertainty regarding fine-tunability
Missing support for Apple Core ML
Poor error handling and lack of progress indicators for CPU-only or non-CUDA environments
Ineffective environment variable handling for local model caching

↓ Weaknesses

No meaningful free tier
API access is newer and more limited than competitors
Less precise control than tools with inpainting/ControlNet
Full FLUX.1 profile →Full Midjourney profile →