Telugu NLP API in India | unoblox

Telugu-language features — support replies, translating product listings, summarising long documents — are usually best served today by a strong general-purpose multilingual model rather than a narrow Telugu-only one. unoblox puts several such models behind one rupee-billed endpoint, so picking a model is a pricing decision, not a procurement one.

Rupee pricing for multilingual models

Model	Input ₹ / 1M tokens	Output ₹ / 1M tokens
Qwen3.8-27B (open weights, vision)	₹16.32	₹48.96
Llama 4 Scout	₹10.08	₹30.24
DeepSeek V3.2	₹26.21	₹38.30
GPT-5 mini	₹25.2	₹201.6
Qwen3 1.7B	Free (₹0)	Free (₹0)

Where teams actually use this

• Drafting and triaging replies to Telugu support tickets.
• Translating product listings and descriptions between Telugu and English for e-commerce.
• Summarising long Telugu documents or call transcripts into a short brief.
• Light content moderation on user-submitted Telugu text, as a first pass before human review.
• Drafting first-pass replies to voice-transcribed Telugu queries that have already been converted to text upstream.

No Telugu-specific model, and that's a fair trade-off

unoblox doesn't have a Telugu-only fine-tuned model, and it wouldn't be honest to imply otherwise. What's on offer instead is a set of general-purpose multilingual models — Qwen3, Llama 4, DeepSeek, GPT — that are commonly used for Indian-language work as part of their broader language coverage. Treat that as a starting point to test against your own text, not a benchmarked guarantee.

Calling the endpoint for Telugu text

curl https://api.unoblox.ai/v1/chat/completions \
  -H "Authorization: Bearer ub-gw-xxxxxxxxxxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen/qwen3.8-27b","messages":[{"role":"user","content":"Translate this product description into Telugu: Lightweight cotton kurta, machine washable."}]}'

As with any non-Latin script, budget for Telugu text to tokenize into more tokens per sentence than English — check actual usage on your invoice rather than assuming parity with an English estimate.

Testing before you commit

Run the same handful of real Telugu inputs — an actual support ticket, an actual product listing — through two or three models from the table above before picking one for production. Because every model sits behind the same endpoint and key, comparing them is a matter of changing the model field in the request body, not standing up a second integration or a second billing relationship.

Frequently asked questions

Do you have a dedicated Telugu model? No. See /models for the current general-purpose catalog.

Which model handles Telugu best? There's no single verified answer — the models in the table above are reasonable starting points to test against your own content.

Does Telugu text use more tokens than the equivalent English text? Often yes, depending on the model's tokenizer. It's a property of how non-Latin scripts get tokenized, not a Telugu-specific charge.

Can I prototype for free before committing budget? Yes, Qwen3 1.7B is free (₹0).

Is the data kept in India? Only select unoblox-hosted small models on unoblox run on India infrastructure. Most catalog models don't guarantee residency — check /models before assuming either way.

What endpoint and authentication do I use? The same OpenAI-compatible /v1/chat/completions endpoint and a single ub-gw-... key used for every other model on the catalog.

Get started in rupees → https://unoblox.ai/sign-in