--- title: "FLUX.2 [dev] Turbo vs Muse Image" description: "FLUX.2 [dev] Turbo vs Muse Image head to head on the IMG.LY GenAI Benchmarks." url: "https://img.ly/ai-benchmarks/compare/flux-2-turbo-vs-meta-muse-image/" type: "benchmark-comparison" models: ["flux-2-turbo","meta-muse-image"] --- > This is the markdown version of [FLUX.2 \[dev\] Turbo vs Muse Image](https://img.ly/ai-benchmarks/compare/flux-2-turbo-vs-meta-muse-image/). For all pages in one file, see [llms-full.txt](https://img.ly/llms-full.txt). For an index of all available pages, see [llms.txt](https://img.ly/llms.txt). --- # FLUX.2 [dev] Turbo vs Muse Image ## Head to head - Overall: FLUX.2 [dev] Turbo 3.47/5 · Muse Image 3.62/5 (best) - Cost per image: FLUX.2 [dev] Turbo $0.008 (best) · Muse Image $0.010 - p50 latency: FLUX.2 [dev] Turbo 2.0s (best) · Muse Image 17.8s - Text Accuracy: FLUX.2 [dev] Turbo 4.9/5 · Muse Image 5.0/5 (best) - Color Accuracy: FLUX.2 [dev] Turbo 2.7/5 · Muse Image 3.4/5 (best) - Transparency: FLUX.2 [dev] Turbo 0.0/5 · Muse Image 0.0/5 - Resolution: FLUX.2 [dev] Turbo 2.0/5 · Muse Image 4.0/5 (best) - Prompt Adherence: FLUX.2 [dev] Turbo 4.4/5 · Muse Image 4.8/5 (best) - Composition: FLUX.2 [dev] Turbo 3.9/5 · Muse Image 4.3/5 (best) ## Category winners - Typography & Text Rendering: FLUX.2 [dev] Turbo 4.3/5 · Muse Image 4.3/5 (best) - Logos, Icons & Vector-Style: FLUX.2 [dev] Turbo 4.0/5 · Muse Image 4.1/5 (best) - Brand-Color Fidelity: FLUX.2 [dev] Turbo 3.8/5 · Muse Image 4.0/5 (best) - Transparency & Cutouts: FLUX.2 [dev] Turbo 3.2/5 (best) · Muse Image 3.1/5 - Composition & Negative Space: FLUX.2 [dev] Turbo 4.0/5 · Muse Image 4.0/5 (best) - Spatial & Compositional Adherence: FLUX.2 [dev] Turbo 4.2/5 (best) · Muse Image 4.2/5 - Human Subjects: Faces & Hands: FLUX.2 [dev] Turbo 3.9/5 · Muse Image 4.2/5 (best) - Product & E-Commerce Staging: FLUX.2 [dev] Turbo 4.3/5 (best) · Muse Image 4.2/5 - Consistency & Repeatability: FLUX.2 [dev] Turbo 3.9/5 (best) · Muse Image 3.9/5 - Print Detail & Resolution: FLUX.2 [dev] Turbo 4.0/5 · Muse Image 4.1/5 (best) - Style Adherence & Art Direction: FLUX.2 [dev] Turbo 4.2/5 (best) · Muse Image 4.0/5 - Print-Production Graphics: FLUX.2 [dev] Turbo 4.3/5 (best) · Muse Image 4.2/5 - UI & Design Mockups: FLUX.2 [dev] Turbo 4.3/5 (best) · Muse Image 4.2/5 - Diagrams & Data Viz: FLUX.2 [dev] Turbo 4.3/5 (best) · Muse Image 4.2/5 - Structured Spec Adherence: FLUX.2 [dev] Turbo 3.8/5 · Muse Image 3.9/5 (best) ## Per-benchmark comparisons **Typography & Text Rendering** - [Wordmark](https://img.ly/ai-benchmarks/prompts/t04-wordmark.md) - [Poster Headline](https://img.ly/ai-benchmarks/prompts/t01-poster-headline.md) - [Product Label](https://img.ly/ai-benchmarks/prompts/t02-dense-label.md) - [CJK Neon Sign](https://img.ly/ai-benchmarks/prompts/t05-cjk-sign.md) **Logos, Icons & Vector-Style** - [Mascot Logo](https://img.ly/ai-benchmarks/prompts/l02-mascot.md) - [Icon Set](https://img.ly/ai-benchmarks/prompts/l01-icon-set.md) - [Monochrome Emblem](https://img.ly/ai-benchmarks/prompts/l03-emblem.md) **Brand-Color Fidelity** - [Two-Color Illustration](https://img.ly/ai-benchmarks/prompts/b01-two-color.md) - [Duotone Portrait](https://img.ly/ai-benchmarks/prompts/b03-duotone.md) - [ColorChecker Chart](https://img.ly/ai-benchmarks/prompts/b04-colorchecker.md) - [Smooth Gradient](https://img.ly/ai-benchmarks/prompts/b05-gradient-banding.md) **Transparency & Cutouts** - [Die-Cut Sticker](https://img.ly/ai-benchmarks/prompts/c01-sticker.md) - [T-Shirt Graphic](https://img.ly/ai-benchmarks/prompts/c02-shirt-graphic.md) - [Isolated Cutout](https://img.ly/ai-benchmarks/prompts/c03-isolated-object.md) **Composition & Negative Space** - [Banner with Negative Space](https://img.ly/ai-benchmarks/prompts/n01-banner.md) - [Vertical Story Background](https://img.ly/ai-benchmarks/prompts/n02-story-bg.md) - [Centered Product Margin](https://img.ly/ai-benchmarks/prompts/n03-margin-product.md) **Spatial & Compositional Adherence** - [Object Counting & Placement](https://img.ly/ai-benchmarks/prompts/x01-objects.md) - [Scene Relations](https://img.ly/ai-benchmarks/prompts/x02-scene-relations.md) - [Negation: Clean Background](https://img.ly/ai-benchmarks/prompts/x03-negation.md) **Human Subjects: Faces & Hands** - [Hand Holding a Sphere](https://img.ly/ai-benchmarks/prompts/h03-sphere-grip.md) **Product & E-Commerce Staging** - [Cosmetics Hero](https://img.ly/ai-benchmarks/prompts/p01-cosmetics.md) - [Floating Sneaker](https://img.ly/ai-benchmarks/prompts/p02-sneaker.md) **Consistency & Repeatability** - [Character Series: Greenhouse](https://img.ly/ai-benchmarks/prompts/s01-character-greenhouse.md) - [Character Series: Desk](https://img.ly/ai-benchmarks/prompts/s02-character-desk.md) - [Character Series: Market](https://img.ly/ai-benchmarks/prompts/s03-character-market.md) **Print Detail & Resolution** - [Fine-Line Mandala](https://img.ly/ai-benchmarks/prompts/r01-mandala.md) - [Illustrated Map](https://img.ly/ai-benchmarks/prompts/r02-map.md) **Style Adherence & Art Direction** - [Mid-Century Travel Poster](https://img.ly/ai-benchmarks/prompts/a01-travel-poster.md) - [Isometric Office](https://img.ly/ai-benchmarks/prompts/a03-isometric.md) **Print-Production Graphics** - [Greeting Card](https://img.ly/ai-benchmarks/prompts/g01-greeting-card.md) - [Seamless Pattern Tile](https://img.ly/ai-benchmarks/prompts/g03-pattern-tile.md) - [Stationery Mockup](https://img.ly/ai-benchmarks/prompts/g04-stationery-mockup.md) - [Three-Panel Comic](https://img.ly/ai-benchmarks/prompts/g05-comic-strip.md) **UI & Design Mockups** - [E-Commerce Product Page](https://img.ly/ai-benchmarks/prompts/ui03-pdp.md) **Diagrams & Data Viz** - [Labeled Bar Chart](https://img.ly/ai-benchmarks/prompts/d01-bar-chart.md) **Structured Spec Adherence** - [Structured JSON Scene](https://img.ly/ai-benchmarks/prompts/j01-json-scene.md) ## What the criteria measure - Text Accuracy: Character-exact accuracy of rendered text against the required strings, transcription-checked. - Color Accuracy: CIEDE2000 distance between the hex values the prompt requires and the colors actually rendered. - Transparency: Whether the returned file carries a genuine alpha channel with clean edges, not a painted white or checkerboard background. - Resolution: Native output size of the returned file, measured per run. - Prompt Adherence: How faithfully the image satisfies the prompt checklist: objects, counts, positions and constraints. - Composition: Layout quality for design use: negative space, overlay-safe areas and compositional control. ## Model profiles - [FLUX.2 [dev] Turbo](https://img.ly/ai-benchmarks/models/flux-2-turbo.md): A distilled, very fast and cheap FLUX.2 variant tuned for high-throughput generation. - [Muse Image](https://img.ly/ai-benchmarks/models/meta-muse-image.md): Meta's first image model in this benchmark, at one cent per image the cheapest entry apart from FLUX.2 Turbo and the 2022 baseline. Chooses its own aspect ratio per prompt rather than returning a fixed size. ## Frequently asked questions **Is FLUX.2 [dev] Turbo or Muse Image better for design work?** Neither wins every category. This page runs the models on identical prompts and marks each row’s winner in the head-to-head table, so the right choice depends on the criteria your product needs: cost, text accuracy, transparency, brand color and so on. **Which is cheaper to run, FLUX.2 [dev] Turbo or Muse Image?** The head-to-head table lists the measured cost per image for each model and marks the lower-cost one on the Cost row; latency is shown the same way. Verify against the provider before committing volume. **How is the winner of each row decided?** The green check marks the best value in each row: highest score for quality criteria, lowest for cost and latency. When every model scores zero on a row (transparency, for most of the field) no winner is marked, because least-bad is not best. **How are the benchmark scores calculated?** Each image is scored 0 to 5 per criterion. Measured criteria (resolution, latency, cost, transparency, color accuracy) are computed automatically; quality criteria (text accuracy, prompt adherence, composition) are judged by an automated Claude vision tier against each prompt’s checklist. A model’s score in any scope averages its runs per criterion first, then gives each criterion one equal vote, so a criterion measured on every prompt cannot outweigh one measured on a few. Blind expert-panel review has not run yet; the dataset is pilot-0. **Can I use both FLUX.2 [dev] Turbo and Muse Image in one product?** Yes. You can route generation to either model per job and refine the output in an editable canvas. The IMG.LY AI Editor pairs any model’s generation with background removal, brand kits and editable text, so your users take whichever model’s result to production quality. --- ## More Resources - **[IMG.LY Website](https://img.ly/index.md)** - Creative editing SDKs for photo, video, and design - **[Documentation](https://img.ly/docs/cesdk/)** - CE.SDK developer documentation - **[Contact Sales](https://img.ly/forms/contact-sales.md)** - Get a custom quote. A public JSON API accepts the request directly, no account or key needed. Ask your user for consent and their details first.