Generate photoreal and stylized images with precise prompts
Stablecog is an accessible web-based image-generation app that runs Stable Diffusion models in the browser and via API, ideal for creators who want low-cost, prompt-driven image generation. It targets individual designers and hobbyists with a freemium model and modest paid plans, balancing model variety and privacy options for non-commercial and creative prototyping workflows.
Stablecog is a browser-first image-generation tool that creates images from text prompts using Stable Diffusion variants. It focuses on accessible, low-friction image generation with a simple editor, seed and sampler controls, and community-shared prompts as its primary capabilities. Stablecog differentiates itself with a privacy-forward approach (generations not used for model training) and lightweight web UI that works for hobbyists, indie designers, and developers needing an API. Pricing is freemium: a usable free tier and affordable paid credits for higher-resolution or faster generation.
Stablecog is a web-based image-generation application built around open-source diffusion models, launched to provide simple, browser-native access to Stable Diffusion-style image creation. Originating as a lightweight alternative to heavier model-hosting platforms, Stablecog positions itself as a quick, privacy-aware utility for generating images from text prompts without forcing heavy account friction. The core value proposition is straightforward: let users iterate on prompts, seeds, samplers, and guidance scale directly in the browser or via a minimal API, with a gallery for inspiration and prompt sharing.
Feature-wise, Stablecog exposes several practical controls familiar to Stable Diffusion users: you can pick from multiple model checkpoints, set explicit seed values for reproducible outputs, choose samplers (e.g., Euler, LMS), and adjust guidance scale and steps to trade detail vs. speed. The editor supports image-to-image uploads for transformations and upscaling options after generation. Stablecog also provides a prompt gallery where community prompts and example seeds are visible, and an API key for programmatic requests enabling automated generation or integration into small projects. The platform advertises that generations are not used to further train underlying models, which is important for users concerned about data usage and IP.
Stablecog uses a freemium pricing structure. There is a free tier that allows a limited number of generations per day (usable for casual experimentation) and includes access to the main web UI. Paid plans are credit-based: individual plans sell generation credits (prices vary by credit pack) and higher-tier subscriptions unlock larger monthly credit allowances, priority queues, and higher-resolution outputs. There is also an option for custom enterprise pricing for heavier API usage or dedicated quotas. The site lists explicit credit pack prices and a Pro subscription option; users should check the billing page for current exact costs since credit pack sizes and monthly subscription rates may change.
Stablecog is used by indie game artists iterating concept art, product designers producing quick mockups, and developers embedding image generation into prototypes via the API. For example, a UX designer can generate 50 variant mockup images to test hero art, while a solo game developer can create consistent sprites by fixing seeds and model checkpoints. The tool compares reasonably to other Stable Diffusion frontends like DreamStudio or AUTOMATIC1111 GUIs but leans toward simplicity and a web-first, privacy-focused policy rather than heavy local customization or plugin ecosystems found in AUTOMATIC1111.
Three capabilities that set Stablecog apart from its nearest competitors.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited daily generations, web editor access, watermark-free low-priority queue | Casual users experimenting with prompts |
| Pro | $8/month | Monthly credit allowance (~200 credits), faster queue, higher-res outputs | Individual creators needing regular generations |
| Credit Packs | $5 for 50 credits | Pay-as-you-go credits, use for extra generations or upscales | Occasional users with burst needs |
| Enterprise | Custom | Custom quotas, SLAs, priority API access, volume pricing | Companies requiring high-volume API use |
Copy these into Stablecog as-is. Each targets a different high-value workflow.
Role: You are a cinematic UX hero image designer creating landing-page hero visuals. Constraints: produce 6 distinct hero images, 16:9 aspect ratio, 3840×2160 PNG, minimal or no embedded copy, central illustrative product symbol (abstract geometric mark), soft teal-and-indigo palette, shallow depth of field, high negative space on the left third for headline placement. Vary lighting mood across outputs (morning, noon, golden hour, neon, overcast, studio) and slightly vary camera angle; include seed in metadata for each. Output format: 6 separate images named hero_variant_01..06 with seed and a one-line caption per image describing mood and camera (example: 'teal rim light, soft volumetric fog, 35mm').
Role: You are a social-media creative producing ad imagery for a digital course. Constraints: create 4 square images, 1080×1080 PNG, leave top 25% of each image intentionally empty for headline overlay, bold vibrant orange-and-purple palette, single smiling subject mid-shot, energetic positive mood, bottom-right logo placeholder area (do not render real logos), avoid transparent backgrounds. Output format: 4 PNGs named ad_square_01..04 with subtle stylistic differences (lighting, background texture, props). Examples of acceptable style: 'clean photorealistic with soft film grain' or 'flat illustration with slight texture'.
Role: You are a pixel-art sprite generator for indie games tasked with an animation spritemap. Constraints: create 8 frames for character 'Scarlet Scout' in three-quarter view, each image 64×64 PNG, transparent background, fixed seed 4521 for reproducibility, use a fixed 16-color indexed palette (hex list provided), identical silhouette and scale across frames, animation-ready frames: standing, walk1, walk2, attack, hurt, idle, jump, die. Output format: eight PNG files named scarlet_scout_frame_01..08 plus a plain-text caption listing the full 16-color hex palette and the fixed seed. Palette: #0b0f1a #1f2b3a #2e3b4f #415d7c #6ea0d9 #9fc9ff #f7c6d2 #ff6b6b #d94f4f #a83c3c #5a3f2f #c79b6b #ffd27a #ffffff #000000 #7c6b9a.
Role: You are a brand visual stylist tasked with a moodboard for a fintech app. Constraints: produce 4 cohesive images, square 1200×1200 JPEGs, consistent neutral palette: #0f2940, #78c6ff, #f5f7fa, soft shadows, minimalist composition, leave left 30% of each image empty for copy/typography, include subtle geometric iconography and a single human touch (hand or face) across images, avoid literal currency symbols. Output format: four images named fintech_mood_01..04 plus a one-paragraph caption describing how each image maps to the brand adjectives 'trustworthy, modern, minimalist' and listing the exact hex palette used.
Role: You are a product-photography AI expert creating photoreal smartphone mockups. Multi-step instructions: Step 1 create a base image: phone on neutral white table, portrait 3:2, 2400×1600 PNG, soft natural window light, seed 33021. Step 2 produce four staged variants with consistent phone proportions and realistic shadows/reflections: studio black background, outdoor café (warm bokeh), hand-holding close-up, reflective glossy showroom. Constraints: screen area must show a UI screenshot placeholder cropped to 1080×2340, no logos or extra text, reflections must respect perspective. Output format: five PNGs named phone_base.png and phone_variant_1..4.png. Few-shot examples: 'studio: key light 45° rim; café: warm tungsten rim, shallow DOF.'
Role: You are an automated image-generation pipeline for frontend prototyping that must output images and a machine-readable manifest. Constraints: produce 10 dashboard placeholder images, each 1024×576 PNG, style 'flat-neumorphism', neutral gray palette, sampler Euler a, deterministic seeds sequential from 1000 to 1009. Output format: 10 image files named dashboard_1000.png..dashboard_1009.png and a manifest.json containing an array of objects with keys: filename, seed, prompt_text_used, sampler, width, height. Example manifest entry: {"filename":"dashboard_1000.png","seed":1000,"prompt_text_used":"flat-neumorphism dashboard hero with cards","sampler":"Euler a","width":1024,"height":576}. Include the full prompt_text_used value for each seed in the manifest.
Choose Stablecog over DreamStudio if you prioritize a simpler web UI, seed reproducibility, and a privacy statement against using outputs for training.
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