Key facts
| Bahasa Indonesia | Latin script, regular spelling and heavy affixation (meN-, -kan, -nya) |
| Register | Standard baku and colloquial Jakarta usage differ — keep one per surface |
| Tokenisation | Affixes and chat abbreviations such as yg and dgn split into subwords — measure with the tokenizer |
| Embeddings | plugsky-embed-multilingual for Indonesian, English and Malay overlap |
| API compatibility | OpenAI-compatible POST https://api.plugsky.com/v1/chat/completions — chat, streaming, JSON mode and function calling |
| Models | 30+ models behind one endpoint, from free tiers to frontier reasoning |
| Free tier | Free plan with plugsky-micro and plugsky-lite, no card required |
| Product status | Chat, streaming, JSON mode, function calling, embeddings, RAG and agents live; audio, images, moderation, files, batch, fine-tuning, assistants and responses coming soon |
TL;DR
- Bahasa Indonesia works on the standard endpoint — no language flag needed.
- Decide baku or colloquial per surface and write it into the system prompt.
- Affixes and chat abbreviations change token counts; measure them.
- Keep Indonesian and Malay evaluation slices separate.
- plugsky-embed-multilingual lets one collection serve Indonesian and English.
How it works, step by step
- List the surfaces you ship (marketing copy, in-app microcopy, support chat) and pick baku or colloquial for each.
- Create a free Plugsky key, set base_url to https://api.plugsky.com/v1 and send representative Bahasa Indonesia prompts to /v1/chat/completions.
- Measure tokens with the tokenizer on real chat text that includes abbreviations such as yg, dgn and nggak.
- Align terminology for product nouns so the model uses your glossary rather than inventing synonyms.
- For RAG, embed documents with plugsky-embed-multilingual and test formal, colloquial and English queries.
- Review outputs with native speakers on a fixed gold set, then move production traffic.
Try it yourself
What AI Bahasa Indonesia means in practice
Indonesian is the official standard, but the language people type online leans on a colloquial register with its own vocabulary, abbreviations and loanwords. A model that writes perfect formal Indonesian can still sound wrong in a chat bubble, and the reverse is true for legal or financial copy.
Treat register as a product decision. Write the expected style into the system prompt, keep a glossary of product terms and approved loanwords, and evaluate output with people who read the register daily. The API itself stays constant: one endpoint, UTF-8 text, no locale parameter.
Tokenization for Bahasa Indonesia text
Spelling is regular and there is no case grammar, so Indonesian usually costs less per sentence than English. The costs hide in affixation: prefixes such as meN- and ber-, suffixes such as -kan and -nya, and chat abbreviations all split into subwords. Numbers written as words are long, and informal text mixes in English terms.
- Count tokens on real chat logs, not on dictionary sentences.
- Decide whether abbreviations stay as typed or get expanded in prompts.
- Keep affixes intact for display; add stemmed keys only for search.
- Re-measure when you switch models — tokenisers differ.
Retrieval and evaluation for Indonesian apps
One multilingual embedding collection can serve Indonesian documents with Indonesian or English queries, and it also handles Malay reasonably well because the languages overlap in structure and vocabulary. That overlap is exactly why evaluation matters: a query in Malay may retrieve Indonesian results for the wrong reason.
- Embed with plugsky-embed-multilingual and keep one model per collection.
- Split the gold set into formal, colloquial and English query slices.
- Add synonym or stemming support for affixed forms in keyword search.
- Test Malay queries separately if your audience spans both markets.
Code example: a Bahasa Indonesia request
Point your OpenAI client at https://api.plugsky.com/v1 and put the register instruction in the system message. Streaming, JSON mode and function calling keep their usual shapes.
client = OpenAI(base_url="https://api.plugsky.com/v1", api_key=os.environ["PLUGSKY_API_KEY"])
client.chat.completions.create(model="plugsky-pro", messages=[{"role": "system", "content": "Gunakan bahasa Indonesia baku yang ramah dan ringkas"}, {"role": "user", "content": "Tulis ulang pesan ini untuk halaman tagihan"}])
Prototype on the free plan with plugsky-micro and plugsky-lite, then compare paid models on your gold set before cutover. See the docs for the full API reference.
Honest comparison
| Capability | Plugsky | Indonesian apps today | Building in-house |
|---|---|---|---|
| API compatibility | OpenAI-compatible — change base_url and model name | Varies by provider and SDK | Full rewrite |
| Register control | Baku or colloquial via system prompts and evals | Depends on provider training mix | You curate and review lexicons |
| Token budget | Fixed tokeniser per model; measure and chunk to fit | Varies by provider and model | You host and tune each tokeniser |
| Multilingual retrieval | plugsky-embed-multilingual for Indonesian and English RAG | Often needs a separate embedding vendor | You serve and maintain embeddings |
| Sovereignty | Cloud, VPC, on-prem and air-gapped with residency options | Usually US/EU public endpoints | You own the full stack |
Frequently asked questions
Can Plugsky generate Bahasa Indonesia?
Yes. Pass Indonesian text in the content field on the standard chat endpoint. Quality varies by model, so compare two or three candidates on your own prompts.
Should my prompts use baku or colloquial Indonesian?
Match the surface: baku for formal and regulated copy, colloquial for chat and consumer flows. State the choice in the system prompt and keep it consistent.
How do I count Indonesian tokens?
Use the tokenizer on real text. Affixes, abbreviations such as yg and dgn, and English loanwords all affect the count, so dictionary sentences mislead.
Does Malay work with the same setup?
Malay and Indonesian are close enough to share a multilingual collection, but vocabulary differs. Keep Malay queries in a separate evaluation slice before assuming coverage.
Is there a multilingual embedding model?
Yes — plugsky-embed-multilingual is part of the 30+ model catalogue and supports cross-language retrieval. Use one embedding model per vector collection.
Can I keep data in my region?
Plugsky supports cloud, VPC, on-prem and air-gapped deployment with residency options; confirm your requirements with the docs and the enterprise team.
Is there a free plan?
Yes — the free plan includes plugsky-micro and plugsky-lite with no card, and a 14-day full-access trial covers the paid catalogue.
How hard is migration from another provider?
Change base_url to https://api.plugsky.com/v1 and map the model name. Streaming, JSON mode, function calling and embeddings keep the same request shapes.