If you’re running a WordPress blog and thinking about going multilingual, chances are you’ve already run into WPML Automatic Translation pricing – and maybe even felt a bit of sticker shock. On paper, WPML looks like the industry standard: powerful, flexible, and deeply integrated with WordPress. But once you actually start translating large amounts of content, the credit-based pricing model can get expensive fast.
For bloggers, content creators, and solo founders (especially men aged 20–40 building content sites or SaaS blogs), this raises a critical question: Is WPML Automatic Translation really worth the cost – or are there smarter, cheaper alternatives?
In this article, we’ll break down exact, real-world costs using a concrete example: 100 000 words (~30 long blog articles). You’ll see how WPML pricing actually works behind the scenes, why costs scale so aggressively, and how modern AI-based solutions can reduce translation costs by hundreds – even thousands – of times.
We’ll also introduce a newer approach: LLM Automatic Translation, a WPML-compatible plugin that uses raw OpenAI API pricing instead of inflated credit systems. If you care about cost efficiency, speed, and SEO-ready translations, this guide will help you choose the right path.
What Is WPML Automatic Translation?
WPML Automatic Translation is a feature built into the WPML multilingual plugin that allows you to automatically translate posts, pages, and other content types without manual copy-paste.
How WPML Automatic Translation Works
WPML connects your WordPress site to external translation engines such as:
When you trigger automatic translation, WPML sends your content to these engines and charges you translation credits based on word count and engine type.
The Credit System Explained
This is where most confusion begins.
- 1 word = 1–4 credits, depending on the translation engine
- Credits are deducted from a monthly free pool (2 000 credits)
- Once exceeded, you pay per 1 000 credits using tiered pricing
The more you translate, the cheaper each credit becomes – but you must cross large usage thresholds to see meaningful discounts.
Pay-As-You-Go vs Prepaid Credits
WPML offers two models:
- Pay-As-You-Go – billed monthly based on usage
- Prepaid Credits – bulk purchase upfront
In both cases, translation costs are separate from the WPML plugin license, which already costs €39–€199/year depending on plan.
The Real Costs of WPML Automatic Translation
Let’s move past theory and look at real numbers.
Example: Translating 100 000 Words
Assume:
- 100 000 words
- ~30 long articles (3 000–3 500 words each)
- One target language
Credit Usage
- Microsoft Translator: 1 credit per word → 100 000 credits
- Google / DeepL: 2 credits per word → 200 000 credits
- PTC: 4 credits per word → 400 000 credits
WPML Pricing Breakdown (Official)
Based on WPML’s official pricing tiers :
| Credits Used | Approx Cost |
|---|---|
| 100 000 credits | ~€57 |
| 200 000 credits | ~€102 |
| 400 000 credits | ~€182 |
👉 Final WPML cost for 100 000 words: €57–€182, on top of your WPML license.
Hidden Costs Most Users Miss
- No cost predictability for growing blogs
- Each new language multiplies costs
- Re-translations (updates) consume credits again
- SEO fields, slugs, and custom fields also count
For content-heavy blogs, WPML pricing quickly becomes a recurring operational expense.
Why Bloggers Find WPML Pricing Too High
For enterprise teams, WPML’s pricing may be acceptable. But for independent bloggers and small publishers, it’s often overkill.
Scaling Becomes Painful
Let’s say you publish:
- 8 articles/month
- 3 000 words each
- 2 languages
That’s 576 000 words/year – easily €1 000+ annually just in translation credits.
Unpredictable Monthly Bills
Unlike hosting or SaaS subscriptions, WPML translation costs fluctuate with content output. This makes budgeting difficult – especially for side projects.
Language Expansion Multiplies Cost
Adding Spanish, German, and French doesn’t just triple reach – it triples translation spend.
Alternative Solutions for Automatic Translation
Several alternatives exist, but most still rely on markup pricing.
TranslatePress & Weglot
- Easier UX
- Subscription-based
- Still expensive at scale
Polylang + External AI
- Flexible
- Requires custom integration
- Not beginner-friendly
LLM Automatic Translation (WPML Extension)
This is where things change fundamentally.
How the 1400× Cheaper AI Approach Works
Instead of selling translation credits, LLM Automatic Translation connects WPML directly to OpenAI’s API.
Raw Token Pricing vs Credits
Let’s reuse the 100 000-word example.
- Average token usage ≈ 1.3 tokens/word
- 100 000 words ≈ 130 000 tokens
Using efficient models (e.g. GPT-5-nano / mini):
- Cost ≈ $0.15 / €0.14
Cost Comparison
| Solution | Cost for 100 000 words |
|---|---|
| WPML Automatic Translation | €182 |
| LLM Automatic Translation | €0.14 |
👉 That’s over 1 200–1 400× cheaper.
No credit packs. No hidden tiers. Just raw AI pricing.
Pro Workflow With LLM Automatic Translation
Seamless WPML Integration
- Works as a WPML extension
- Translates posts, pages, CPTs
- Supports Gutenberg & Elementor
Context-Aware Translations
You can define:
- What your website is about
- Target audience
- Writing style
This dramatically improves translation quality compared to generic engines.
SEO-Ready Output
- Compatible with Yoast SEO & Rank Math
- Translates meta titles, descriptions, slugs
- No broken layouts or formatting
Quality Comparison: WPML vs AI Translation
Common Myth: “AI Translations Are Worse”
In reality:
- WPML uses rule-based or statistical engines
- Modern LLMs understand context, tone, and intent
For blogs and content sites, AI translations often sound more natural, especially with context enabled.
Real-World Use Case
100+ websites already use LLM Automatic Translation for:
- Content marketing blogs
- SaaS documentation
- SEO landing pages
When WPML Automatic Translation Still Makes Sense
To be fair, WPML isn’t “bad”.
WPML Automatic Translation is still a good choice if you:
- Run a large enterprise site
- Need strict glossary enforcement
- Have budget predictability > cost sensitivity
But for bloggers and creators, the economics simply don’t make sense.
Quick Takeaways
- WPML Automatic Translation pricing scales poorly for content-heavy sites
- 100 000 words can cost €182 in WPML credits
- AI-based translation can cost ~€0.15 for the same volume
- That’s over 1 400× cheaper
- LLM Automatic Translation works inside WPML
- Context-aware AI produces more natural results
- Ideal for bloggers, SEO sites, and SaaS content
Conclusion
WPML Automatic Translation pricing isn’t inherently wrong – but it’s built for a different era. An era before large language models made high-quality translation cheap, fast, and programmable.
If you’re a blogger publishing tens or hundreds of thousands of words per year, continuing to pay hundreds of euros for automated translations simply doesn’t make economic sense anymore. Especially when the same – or better – quality can be achieved for literal cents.
The combination of WPML + LLM Automatic Translation gives you the best of both worlds: WPML’s mature multilingual framework and AI’s radically lower costs. No copy-paste workflows. No credit anxiety. Just scalable multilingual content.
👉 If you’re serious about international SEO and cost efficiency, it’s time to rethink how you translate WordPress.
FAQs
Is WPML Automatic Translation worth the price?
For small sites – maybe. For blogs with large content volumes, it becomes very expensive compared to AI-based alternatives.
How much does WPML Automatic Translation cost per word?
Roughly €0.0008–€0.0018 per word, depending on engine and volume .
Can I use AI with WPML?
Yes. Plugins like LLM Automatic Translation integrate directly with WPML and replace the credit system.
Is AI translation safe for SEO?
Yes, when metadata, slugs, and structure are preserved. LLM Automatic Translation is compatible with Yoast and Rank Math.
Do I need an OpenAI account?
Yes. You use your own API key, meaning full control and transparency over costs.
