EvoLink.ai

The AI API gateway for developers who hate overpaying.
One key → GPT-5.2, Claude, Seedance 2 & 100+ models
up to 70% less.
start free at

[EvoLink.ai @EvoLinkAi]

For API builders, we also maintain a Midjourney API repo for production workflows.

Inside:
pricing notes
async task flow
cURL, Python, and JavaScript examples
callbacks
generation and editing workflow docs

https://t.co/Umi2N31E8M

[EvoLink.ai @EvoLinkAi]

Midjourney V8.1 is now the default model on Midjourney.

For image builders, the practical upgrade is simple:

faster iteration, native 2K HD output, better prompt adherence, stronger text rendering, and more stable style reference workflows.

[EvoLink.ai @EvoLinkAi]

What changed in V8.1:

1️⃣SD images in about 4s
2️⃣HD images in about 12s
3️⃣HD renders at 2K without upscaling
4️⃣srefs and moodboards are more stable
5️⃣image prompts and image weights are back
6️⃣Prompt Shortener and Describe are improved

try it in our playground $0.079/image

https://t.co/QpHle19uNU

[EvoLink.ai @EvoLinkAi]

@chenzeling4 provider lock-in is exactly the pain point. a clean API layer makes it easier to swap models and keep the same workflow. EvoLink has GPT Image 2 access here: https://t.co/UhHuXYVYv5

[EvoLink.ai @EvoLinkAi]

@synthden that hidden-cost problem is real. video tools look cheap until subscriptions, credits, retries, and failed renders stack up. EvoLink keeps Kling API access pay-as-you-go here: https://t.co/Z7IT9YHMo5

[EvoLink.ai @EvoLinkAi]

@TrevorTardif this is the exact pain point: AI video is usable, but the workflow cost is hidden in all the tool switching and retries. if you want Seedance as a direct API step, EvoLink has it here: https://t.co/ufVmjnFZnL

[EvoLink.ai @EvoLinkAi]

@bulbul017707 agree that workflow is the bigger change than prettier clips. when the loop is script -> frames -> video -> revisions, direct API access becomes useful. Seedance 2.0 is available here: https://t.co/ufVmjnFZnL

[EvoLink.ai @EvoLinkAi]

@FindLogan @pingToven that is the exact reason I like routing layers: one API key, multiple models, and less card sprawl. if you specifically want Seedance 2.0 API access, EvoLink has it here: https://t.co/ufVmjnFZnL

[EvoLink.ai @EvoLinkAi]

Try GLM-5.2 on EvoLink.

Log in, test it in your own workflow, and compare it with the models already in your stack.

15% off available for this launch.

https://t.co/9QPdcGf9df

[EvoLink.ai @EvoLinkAi]

GLM-5.2 is now available on EvoLink.

A text model built for long-context coding, repo-scale work, and agentic developer workflows.

Use it when your task is bigger than one file: refactors, migrations, debugging loops, and multi-step automation.

[EvoLink.ai @EvoLinkAi]

What stands out:

1️⃣1M-token context support
2️⃣High / Max reasoning effort modes
3️⃣Long-horizon coding workflows
4️⃣Agent-friendly setup for existing coding tools

over 50 use cases of GLM 5.2 collection
https://t.co/LAfazYPJ2a

[EvoLink.ai @EvoLinkAi]

@skipday_io that design-reference gap usually comes from turning the image into text first. keeping direct image-in generation behind one API layer tends to preserve layout better. GPT Image 2 here: https://t.co/0JMphkQijz

[EvoLink.ai @EvoLinkAi]

@DataJuggler007 @0xInk_ credit expiry is exactly why I’d measure cost per usable clip instead of plan marketing. keeping Kling behind an API layer also makes provider swaps easier when those rules change: https://t.co/4f9w8H93U4

[EvoLink.ai @EvoLinkAi]

@HPCAITech yeah, the routing layer is where cost, fallback, and workload shape actually get decided. for video stacks, keeping Seedance behind one gateway gets pretty useful fast: https://t.co/eR9bk3XP8e

[EvoLink.ai @EvoLinkAi]

@BombGirlsClub @Dokko57932483 yeah, mini is the lighter tier. good for exploration, then full 2.0 still makes more sense for keeper shots with heavier motion. you can check direct API here: https://t.co/fRb2rAmpR5

[EvoLink.ai @EvoLinkAi]

@MrJ0SHie yeah, credits hide the real unit cost fast. I’d benchmark price per usable second across providers instead of headline plan size. this price breakdown may help: https://t.co/QOjBQpylkq

[EvoLink.ai @EvoLinkAi]

@stretchcloud video as code is the part most teams skip. once captions, revisions, and variants need to stay deterministic, keeping the render step behind an API helps a lot. this workflow repo may help: https://t.co/JXsoopO3c1

[EvoLink.ai @EvoLinkAi]

@prodialabs for this kind of product/image workflow, API access is the difference between one-off demos and repeatable production. Nano Banana API is here: https://t.co/LGg16EZCpU

[EvoLink.ai @EvoLinkAi]

@adityarao310 image model UX gets much easier when retries and provider quirks sit behind one API boundary. GPT Image 2 via EvoLink is worth testing for that: https://t.co/yZmIB5Lvno

[EvoLink.ai @EvoLinkAi]

@r1ckp this is exactly where routing matters: ideation, frames, video, upscale, and lipsync may each need a different model. I’d keep that pipeline API-first: https://t.co/2keeMzInV6