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AI Sticker Generator on Martini
Indie creator launching a 24-sticker Telegram pack for fans and every sticker needs to descend from one consistent character with a transparent background. Drop the character reference once, fan across Flux, Nano Banana 2, Midjourney, GPT Image 2, and Seedream for expression range, chain through background-removal for transparent cutouts, and export 512x512 WebP files ready for the Telegram @Stickers bot upload flow.
What this feature solves
Sticker packs are how a fandom develops shared language. An indie creator launching a 24-sticker Telegram pack — for fans of a webcomic, a podcast, a niche community — needs every sticker to feature the same character in 24 different moods, poses, and reactions. Each sticker has to ship at 512x512 with a clean transparent background, package as a coherent pack, and follow the platform's sticker-pack format. Doing that 24 times across separate AI image sessions is the fast path to character drift, mismatched edges, and a pack that reads as a stack of unrelated illustrations.
Tab-based sticker tools force the creator into a one-sticker-at-a-time loop with no upstream character anchor. Each new generation drops the reference, the background-removal step happens manually in another tool, the 512x512 resize happens manually in a third tool, and the pack metadata gets assembled by hand. By sticker number 18 the creator has lost track of which model produced which expression, the character has drifted on outfit and color, and the pack visibly fragments compared to the first six stickers.
And there is the platform-format gap. Telegram wants 512x512 WebP with transparent background, packaged through the @Stickers bot. WhatsApp wants 512x512 WebP under 100KB per sticker, packaged through a Sticker Maker app. iMessage wants 408x408 PNG packaged through Xcode. Discord wants 320x320 PNG/APNG/Lottie depending on tier. Generic AI image tools produce a generic 1024x1024 image; the creator still has to run background removal, resize, and reformat per platform. The chain that produces a clean, multi-platform sticker pack is exactly what tab-based tools cannot express.
Why Martini is different
Martini anchors the character once on the canvas. Drop the character reference image as a single labeled image node — the webcomic protagonist, the podcast mascot, the brand fan-character. Every per-sticker prompt (laughing, crying, confused, sleeping, thumbs-up, eating, working, dancing, vacation, holiday) wires into the same anchor. The 24-sticker pack becomes a fan-out from one upstream character node, and every reaction descends from the same source — visual identity holds across the entire pack automatically.
Multi-model fanout for expression variety, single-model for the catalog scale-out. Run the first three stickers in parallel across Flux, Nano Banana 2, Midjourney, GPT Image 2, and Seedream from the same character anchor. Pick the strongest model for character fidelity at sticker scale (typically Nano Banana 2 for mascot-style detail) and lock it for the remaining 21. Background-removal happens inline as a tool node — every sticker chains through it without a manual round-trip to another app. The character stays consistent, the transparent edges land clean, and the pack ships as one canvas.
Downstream chaining handles platform formats. Once the 24 stickers land with transparent backgrounds, fan out into platform-specific exports — 512x512 WebP for Telegram and WhatsApp, 408x408 PNG for iMessage, 320x320 PNG for Discord. The same approved character pack produces every platform variant from one canvas. The creator uploads through Telegram @Stickers bot, WhatsApp Sticker Maker, Xcode for iMessage, or Discord server settings — Martini does not auto-publish to any of them, but the canvas produces the file bundle ready for each platform's own publishing flow.
Common use cases
Telegram fan pack for an indie webcomic
Webcomic creator anchors the protagonist once and fans 24 expressions of the character into a Telegram pack for the fanbase to share.
WhatsApp sticker pack for a podcast community
Podcast launches a 16-sticker pack with the host caricature in different reactions; fans share clips and reactions in WhatsApp groups.
iMessage sticker pack for a brand or product fandom
Brand with a recognizable character launches an iMessage pack — sticker tray, sticker pack, App Store listing — packaged through Xcode.
Discord pack for a game or community server
Game community moderator generates a sticker set tied to in-game lore — boss reactions, victory cheers, raid outcomes — for use across the server.
Holiday or seasonal expansion to an existing pack
Existing pack creator adds a Halloween, holiday, or summer drop — same character, seasonal variations, locked to the original pack template.
Brand sticker pack as part of a product launch
Consumer brand with a recognizable mascot ships a free sticker pack alongside the product launch — community asset, viral potential, on-brand.
Recommended model stack
flux
imageHigh-fidelity character renders that hold detail at sticker scale and survive background-removal cleanly.
nano-banana-2
imageReference fidelity that keeps the same character across every expression at 512x512 sticker scale.
midjourney
imageStylistic range and expressive composition for illustrative sticker reactions.
gpt-image-2
imageEdit-aware refinement to clean expression details and edge quality before background-removal.
seedream
imageEditorial variation for sticker packs that need a more graphic or illustrated direction.
How the workflow works in Martini
- 1
1. Anchor the character reference once
Drop one clean reference image of the pack character as a labeled image node. Every sticker in the pack inherits from this single source.
- 2
2. List the 24 expressions and reactions as prompts
Write out the expression list — laughing, crying, confused, sleeping, thumbs-up, eating, working, dancing, vacation, holiday, surprise, love, applause, victory, deadline, snack, weekend, salute, suspicious, sleepy, fire, prayer, eye-roll, vacation.
- 3
3. Fan out the first three reactions across multiple models
Run the first three expressions in parallel across Flux, Nano Banana 2, Midjourney, GPT Image 2, and Seedream from the same character anchor. Compare takes; lock the winning model for the rest of the pack.
- 4
4. Run the remaining 21 reactions through the locked model
Lock the strongest model (typically Nano Banana 2 for character fidelity) and run the remaining 21 expression prompts through it from the same anchor.
- 5
5. Chain through background-removal for transparent cutouts
Wire each finished sticker through the background-removal tool node. Review hair-edge artifacts and re-run if the cutout fights the character silhouette.
- 6
6. Fan into platform format exports
Once cutouts are clean, export 512x512 WebP for Telegram and WhatsApp, 408x408 PNG for iMessage, and 320x320 PNG for Discord. Each platform variant comes from one approved sticker.
- 7
7. Hand off to the platform-specific publishing flow
Telegram via @Stickers bot, WhatsApp via Sticker Maker app, iMessage via Xcode submission, Discord via server settings. Martini produces the files; the creator handles platform publishing.
Example workflow
Yuna is an indie webcomic creator launching a 24-sticker Telegram pack featuring her protagonist Mio — a teen detective with a signature trench coat. She opens a workspace canvas and drops the canonical Mio illustration as the upstream character anchor. She lists 24 expressions in a text node — laughing, magnifying-glass-investigating, crying, asleep-on-a-case-file, eureka, suspicious, thumbs-up, eating-bento, exhausted, victory, oversleeping, cold-coffee, on-the-phone, taking-notes, raining, sunny-day, dancing-celebration, scared, eye-roll, applause, vacation, snowy, holiday, salute. She runs the first three across Flux, Nano Banana 2, Midjourney, GPT Image 2, and Seedream; Nano Banana 2 holds Mio's trench coat and proportions best at sticker scale. She locks Nano Banana 2 for the remaining 21. Each sticker chains through background-removal for transparent edges, then into a 512x512 WebP export for Telegram and a 408x408 PNG export for iMessage (a future sub-pack). The canvas produces a 24-sticker bundle ready for upload. Yuna runs the pack through Telegram's @Stickers bot, names it 'Mio Pack vol. 1,' and shares the pack link in her newsletter. Fans download and share within the day.
Tips and common mistakes
Tips
- Pack narrative beats random variety. 24 expressions of one character beat 24 unrelated stickers — the pack tells a story together.
- Use Nano Banana 2 for character fidelity at 512x512. The cutout step is unforgiving; Nano Banana 2 holds detail through it.
- Check hair-edge artifacts after background-removal. Wispy hair, fur, and fabric edges sometimes need a manual re-run or a contrast tweak before they cut clean.
- Telegram and WhatsApp prefer the same 512x512 WebP base; iMessage and Discord need separate format passes. Build the pack at the highest spec, downsize per platform.
- Save the canvas as a pack template. Holiday or seasonal expansions next year inherit the locked character anchor and the proven model chain.
Common mistakes
- Using copyrighted characters as the pack subject. Pikachu, Mickey, Marvel, anime IP — all off-limits for sticker packs that ship to a public sticker store.
- Generating real-person stickers without explicit consent. Caricatures of public figures or competitors invite likeness-rights problems.
- Promising auto-publish to Telegram, WhatsApp, iMessage, or Discord. Martini produces the files; the creator uploads through @Stickers bot, Sticker Maker, Xcode, or server settings respectively. Each platform also has its own content rules.
- Skipping the background-removal review. Hair, fur, and fabric edges sometimes leave artifacts that fight the cutout — review every sticker before exporting the pack.
- Letting character drift across the pack. Without a single locked anchor, sticker 18 looks like a different character than sticker 1, and the pack fragments visibly.
Related how-to guides
Related models and tools
Tool
AI Background Removal
Remove backgrounds from images for assets and compositing on Martini.
Tool
AI Image Upscaling
Upscale images and keyframes before final video generation on Martini.
Provider
Google's Veo video, Imagen image, and Nano Banana model workflows on Martini.
Provider
OpenAI
OpenAI's GPT Image and Sora video model workflows available on Martini.
Provider
ByteDance
ByteDance's Seedance video and Seedream image model families on Martini.
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Related docs
Related reading
Comparisons
Frequently asked questions
Can I publish AI stickers directly to Telegram or WhatsApp?
Martini produces the platform-specced files (512x512 WebP for Telegram and WhatsApp, 408x408 PNG for iMessage, 320x320 PNG for Discord). The actual pack publishing happens through each platform's own flow — Telegram's @Stickers bot for Telegram, the Sticker Maker app for WhatsApp, Xcode for iMessage App Store submission, and server settings for Discord. Martini does not auto-publish; the canvas produces the bundle.
How do I keep all 24 stickers looking like the same character?
Anchor the character reference image once on the canvas as the upstream node. Every per-sticker expression prompt wires into the same anchor — the model receives the character as the consistent visual source and the expression as the per-sticker variable. Lock Nano Banana 2 as the model after a fan-out test on the first three stickers; it holds character fidelity across the pack better than peers.
What sizes and formats do the platforms need?
Telegram: 512x512 WebP with transparent background, packaged via @Stickers bot. WhatsApp: 512x512 WebP under 100KB per sticker, packaged via Sticker Maker. iMessage: 408x408 PNG, submitted via Xcode. Discord: 320x320 PNG, APNG, or Lottie depending on server boost tier. The canvas produces all of these from one approved sticker.
Can I use a copyrighted character as the pack subject?
No. Generating Pikachu, Marvel, Disney, anime IP, or any registered character as a sticker pack is a copyright and trademark violation, even if the pack ships free. Build packs around your own brand mascot, original characters, or fully licensed IP. AI image models will happily produce copyrighted characters; using them is on you.
How do I handle hair-edge artifacts from background removal?
Review every sticker after the background-removal pass. Wispy hair, fur, fabric edges, and small accessories sometimes leave halo or fringe artifacts. For problematic stickers, re-run the cutout against a higher-contrast generation or pipe through GPT Image 2 with an edge-cleanup prompt before the final export.
Which model is best for stickers?
For character fidelity across a 24-sticker pack at 512x512, Nano Banana 2 leads. Flux holds high-detail expressions strongly. Midjourney brings illustrative range. GPT Image 2 refines the strongest expressions. Seedream offers editorial variation. Fan out the first three stickers across all five, pick the model that holds the character best, and lock it for the remaining pack.
Build it on the canvas
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