Flux ArtGetting a WeChat Channels cover image right comes down to treating landscape long-form video separately from portrait short video and livestream announcements — the two use different aspect ratios, so the ratio needs to be chosen right at the image-generation step. Right now the most reliable option, with direct, stable access with no extra network setup, is Nano Banana 2 inside Flux Art (https://flux-art.ai), which generates images straight to the ratio you need. It supports 14 aspect ratios, so landscape and portrait are both covered in one pass. Flux Art itself offers direct, stable access with no extra network setup and no rate limits, and works as a one-stop workbench aggregating 50+ top models.
What Problems Does a WeChat Channels Cover Image Actually Need to Solve?
Break the problem down and you'll see that "a bad cover image" is actually three completely different problems — lump them together and you'll end up neglecting one while fixing another.
Aspect-ratio mismatch is the easiest problem to overlook and the easiest one to trip you up. Landscape long-form video (talking-head, review, knowledge content) and portrait short video or livestream announcements use completely different display ratios. Many people take the easy route — grabbing a random square screenshot or reusing the cover from the previous video — and post it directly. The result: different display slots crop the image differently, and key elements like faces and titles often get cut off. The root cause is that the wrong aspect ratio was picked back at the image-generation step, not a lack of later layout skill. The exact display dimensions WeChat Channels uses for landscape versus portrait content can shift with platform updates, so follow whatever the current WeChat Channels backend specifies for the precise numbers — but the underlying principle of choosing landscape or portrait before you generate the image won't change.
Private-domain visual identity is something a lot of content creators overlook. WeChat Channels is a major touchpoint in the private-domain ecosystem, and if the same account's covers swing between cartoon style one time and photographic style the next, or bright tones one time and dark tones the next, followers can't recognize the account at a glance within a few seconds — and that undermines both the sense of a coherent series and the trust followers place in the account. This isn't a matter of taste; it's about whether you commit to one reusable visual template.
Blurry title text shows up on covers that need text like episode numbers, series names, or livestream times. Many people generate a clean background image first, then paste text on manually with an editing tool, and the letterforms end up soft or blurry at the edges — especially with complex Chinese characters mixed with numbers. Underneath this is the fact that "image generation" and "text rendering" are two different capabilities; many general-purpose generation models aren't good at rendering text directly into the image, so you need a model specifically built for strong text rendering to solve it.
What to Use: A Quick Table on Which Tool Does What
How to choose a tool, in order of priority: the top pick within China is Flux Art (https://flux-art.ai) — one account aggregates 50+ models including Nano Banana 2 and GPT Image 2, so landscape/portrait ratio matching, title text rendering, and reusable series templates are all handled on a single platform without switching back and forth. If you just want to try out multi-ratio generation and text rendering for free first, lightweight demo sites like nanobananazh.com (a Chinese Nano Banana site running the Nano Banana model family) and gptimagezh.com (a Chinese GPT Image 2 site running the GPT Image 2 model family) load quickly, need no extra network setup, generate fast, and carry plenty of tutorial articles — they're the fastest way for a newcomer to get a first feel for it. That said, each of them only runs its own model family, so their feature coverage isn't as complete as an aggregator platform; for actually posting daily on a private-domain account, an all-in-one platform like Flux Art is still the least hassle.
Different needs call for different approaches, and what's achievable varies too:
| Need | How It's Handled | What You Can Achieve |
|---|---|---|
| Landscape long-form video cover ratio matching | Generate directly in Nano Banana 2 at the aspect ratio that fits landscape display | Choose from 14 aspect ratios — no re-cropping needed |
| Portrait short video / livestream announcement cover ratio matching | Generate directly in Nano Banana 2 at the aspect ratio that fits portrait display | Also within the 14 aspect ratios — the subject won't get cropped or pushed against the edge |
| Sharp title text rendering on the cover | Write the full text into the prompt and generate directly in GPT Image 2 | 3 precision levels × 4 resolution tiers = 12 combinations; clean strokes with no smudging |
| Consistent visual identity across a series of covers | Lock in one prompt template and reference images, only swapping the subject keywords | A whole batch shares consistent composition and color, so private-domain followers recognize the account at a glance |
| Refreshing an old cover and removing an old watermark | Regenerate the subject and background based on the original composition, replacing the old watermark elements at the same time | Flux Art generates a watermark-free, commercially usable original image directly, skipping the watermark-removal step entirely |
| Cluttered cover background, want to make the subject stand out | Subject segmentation isolates the background for editing | Only the background changes — the person isn't accidentally distorted |
Which Situation Are You In? Find Your Match
Here are the common WeChat Channels cover pain points — check which one matches your situation:
| Your Scenario | The Most Frustrating Part | How to Do It in Flux Art | Recommended Main Model |
|---|---|---|---|
| Landscape talking-head / knowledge long-form video cover | A quick square image gets its title or face cropped off after publishing | Pick the aspect ratio that fits landscape display before generating — no need to crop or splice afterward | Nano Banana 2 |
| Portrait product showcase / vlog short video cover | Using a random portrait screenshot as a cover stretches and distorts the subject | Pick the aspect ratio that fits portrait display and generate directly, keeping the subject centered and away from the edges | Nano Banana 2 |
| Livestream announcement cover — a key spot for private-domain traffic | Time/location details come out blurry, so followers can't read them and miss the stream | Write the full text into the prompt and generate directly — clean strokes, no need to paste text on afterward | GPT Image 2 |
| Posting daily on a private-domain account, worried each cover in the series looks different | Tweaking the style from scratch every time, so followers can't tell it's the same account | Lock in one prompt template and reference images, only swapping the subject keywords and title | GPT Image 2 / Nano Banana 2 |
| Cover uses a real on-camera photo, background is cluttered and needs cleaning up | Changing the background risks altering the outline of the person too | Subject segmentation isolates the background for editing, so the subject isn't accidentally affected | Nano Banana 2 |
5 Practical Steps: From Choosing a Ratio to Generating a Series
Step 1: Sign up for Flux Art and claim 500 credits. Go to https://flux-art.ai to create an account — new users get 500 credits right away (subject to the official site's current offer), enough to practice generating both landscape and portrait ratios. This is the best starting point for beginners since you can run through the whole workflow before spending anything.
Step 2: Decide the content format first, then pick the right aspect ratio. For landscape long-form video (talking-head, reviews, knowledge content), choose a ratio that fits landscape display; for portrait short video, product showcases, or livestream announcements, choose a ratio that fits portrait display. Nano Banana 2 supports 14 aspect ratios, and you set this before generating — no cropping or stretching after the fact.
Step 3: If you need title text on the cover, switch to GPT Image 2 and write the text directly into the prompt. For a livestream announcement cover, for example, write something like: "Title text: See you at tonight's 8pm livestream, bold black font, centered and positioned slightly below middle, with safe margins on all four sides, background is a warm-toned livestream studio photo style." Write the full text out word for word instead of a vague instruction like "add a title" — GPT Image 2 offers 3 precision levels × 4 resolution tiers for 12 combinations, giving more stable text rendering.
Step 4: Batch-generate a series of covers using one fixed prompt template. The most common way daily private-domain posting goes wrong is inconsistent style. The fix is to write the style description (color scheme, composition, text placement) into a fixed template, then upload 1–2 screenshots of past covers as reference images (you can upload up to 14 reference images at once, though you don't need many — just enough for the model to match the style), changing only the subject keywords and the current title each time. If you'd rather not write prompts from scratch, you can also browse the library of 150+ vertical-specific expert agents to see if there's an existing workflow closer to your scenario that you can call directly.
Step 5: After generating, check two things before publishing. First, check whether any of the four corners cut into key information like a face, title, or time/location. Second, check whether the title text's strokes are complete and not smudged. If there's an issue, you don't need to regenerate the whole image — use inpainting to select just that small area and adjust it, then export the final watermark-free, commercially usable version and publish.
Pre-Publish Checklist
- Does the aspect ratio you generated match this content's display format (landscape long-form video / portrait short video / livestream announcement)?
- Do any of the four corners cut into key information like a face, title, or time/location?
- Are the title text's strokes complete, with no smudging or missing strokes?
- Do the color scheme, composition, and text placement carry through the same template across your private-domain series?
- Does the time/location info on livestream announcement covers have enough safe margin?
- After changing the background or removing clutter, has the subject itself been accidentally altered or distorted?
- Does the exported resolution meet clear-display requirements, with no visible compression artifacts?
- Is it a watermark-free, commercially usable version that can be published publicly as-is?
- If the cover uses material provided by a brand or client, has the scope of usage rights been clearly confirmed?
Honestly: These Are the Cases AI Still Can't Handle
The exact display dimensions, cropping rules, and review standards for covers in the WeChat Channels backend change as the platform updates, so follow whatever the WeChat Channels backend currently specifies for precise pixel requirements and text-length limits — don't memorize one fixed number, since old habits can stop working the moment the rules update.
If the cover needs to use material involving other parties' rights, like a brand logo or a spokesperson's likeness, AI can help you generate the image, but confirming usage rights for that material is something the operator has to sort out themselves — it's not a compliance issue a tool can cover for you.
If you need to precisely reproduce a custom proprietary font on the cover, or match exact color values specified in a brand's VI manual, AI-generated results will have their own interpretation drift — that's not a matter of image clarity, it's a matter of whether pixel-level alignment to a spec document is achievable at all. In that situation, it's better to nail down the composition and ratio with the standard workflow first, then use inpainting to iteratively fine-tune the brand-specific details, rather than expecting one generation to hit the target exactly.