Can Whisper transcribe Tamil offline?

Yes: Tamil is in Whisper’s list and large-v2 scored 17.5% word error rate on read FLEURS sentences. A Whisper model scored 78.4% on natural Tamil speech in the IndicVoices paper, so test on real meetings.

Why does Whisper do better on Tamil than on other Indian languages?

The paper names no cause for Tamil, but it finds that error rate tracks training hours closely (a squared correlation of 0.83), and Tamil has 136 hours against 12 for Hindi and 4.3 or less for Telugu, Kannada and Bengali.

Which open models list Tamil?

Qwen3, IndicConformer, IndicTrans2, NLLB-200, Meta MMS, and Sarvam’s smaller models all list Tamil. Meta’s Llama 3.3 and Llama 4 cards do not, and Gemma’s cards say over 140 languages without a list.

How good is offline Tamil translation?

IndicTrans2 scored 39.1 chrF++ from English to Tamil and 45.8 from Tamil to English on conversational sentences, close to NLLB 1.2B distilled at 37.2 and 45.7. The scores are overlap measures, so have a Tamil reader check anything official.

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ANVE

Offline AI in your language · updated 2026-10-16

Can offline AI handle Tamil?
தமிழ் in speech, text and translation: the Indian language Whisper heard most, and where it still falls short.

Short answer. Yes for read speech, with care for natural speech. Tamil is the Indian language Whisper’s paper gives the most training audio: 136 hours, with a 17.5% word error rate on read FLEURS sentences (large-v2) and 16.1% on Common Voice 9. But on natural speech in the IndicVoices paper a Whisper model scored 78.4% and AI4Bharat’s IndicASR 31.2%, so read-speech figures overstate what a meeting will give you. Qwen3 lists Tamil; Meta’s Llama cards do not. IndicTrans2 scored 39.1 chrF++ from English to Tamil on conversational sentences. ANVE has not tested Tamil yet. Coverage and figures are as of October 2026.

What open models cover in Tamil

Task	Models	What the source says
Speech to text: Whisper	Whisper large-v2, large-v3	The Whisper paper counts 136 hours of Tamil speech with Tamil transcripts, the most of any Indian language in it, and 1,484 hours paired with English text. Large-v2 scored 17.5% word error rate on FLEURS and 16.1% on Common Voice 9, both read speech. The large-v3 card gives no Tamil figure.
Speech to text: Indian-language models	IndicConformer, IndicWhisper, Meta MMS	IndicConformer lists Tamil (MIT licence). IndicWhisper averages 25.3% across its Tamil test sets, which differ from the Whisper paper’s, so the two figures are not comparable. IndicVoices, natural speech: IndicASR 31.2% (trained on 100 hours of Tamil), MMS 75.4%, Whisper 78.4%.
Chat, summaries, drafting	Qwen3, Gemma, Sarvam, Llama	Qwen3’s launch post lists Tamil among its four Dravidian languages. The Llama 3.3 and 4 cards and the gpt-oss card list or test no Tamil. MILU (2024 test, Indian exam questions; open base models, 5-shot): Llama 3.1 70B 60.7%, Gemma 2 27B 58.6%; the paper notes low accuracy in agglutinative languages such as Tamil and Telugu. Sarvam-1 and Sarvam-M name Tamil.
Translation	IndicTrans2, NLLB-200	IndicTrans2 paper (2023), conversational set (IN22-Conv), chrF++: English to Tamil 39.1, Tamil to English 45.8; NLLB 1.2B distilled 37.2 and 45.7. On web and Wikipedia sentences (IN22-Gen) the scores are 49.5 and 59.8, so conversational Tamil is the harder test.

Tamil script, Tamil Nadu and beyond

Tamil (தமிழ்) has its own script. The 2011 Census counted 6,90,26,881 people with Tamil as their mother tongue, 5.70% of India and the fifth largest group. Tamil Nadu had 6,37,53,997. Karnataka had 21,10,128, Puducherry 11,00,976, Andhra Pradesh (as in 2011) 7,13,848, Maharashtra 5,09,887 and Kerala 5,02,516. The Census counts people in India only.

The 17.5% is for read sentences. A Whisper model of unstated size scored 78.4% in the IndicVoices test, where most speech is unscripted. Whisper’s paper finds that a language’s error rate tracks its training hours closely, and Tamil’s 136 hours put it well ahead of Hindi’s 12. But its test sets are read sentences, so the 17.5% says little about unscripted meeting speech.

If your staff mix English into Tamil sentences, test the mix. None of the sources reports mixed-language Tamil results.

For English meetings, the Svarah paper measured Whisper large at 5.3% word error rate on speakers whose mother tongue is Tamil, the same as native Hindi speakers (5.3%).

What to test before you rely on it

Record spontaneous meetings, not read-aloud text. The gap between 17.5% and 78.4% above is the reason.
Read a sample for dropped or wrong word endings. Tamil builds long words by adding endings, and the MILU paper notes weaker results in such languages.
Check numbers, rupee amounts and dates, and whether digits come out as Tamil words or as numerals.
Test speakers from Tamil Nadu and from Karnataka, Puducherry and Kerala, where the Census shows lakhs of Tamil speakers.
Translate a notice in both directions and ask a Tamil reader to mark errors. The conversational scores are low for every system in the IndicTrans2 table.

Where ANVE stands

ANVE’s meeting-minutes maker handles Hindi, English and Hinglish today. Tamil has not been tested on ANVE yet, so there is no ANVE result to report and nothing here promises support.

A better Tamil model would reach an ANVE box as an update. At present ANVEAI installs updates on site, signed packages applied offline by USB are not on ANVE yet, and ANVE never updates itself over the internet.

A demo call is free. If Tamil decides your purchase, ask for your own recordings to be tried before you commit, and judge the transcript line by line.

Questions people ask

Can Whisper transcribe Tamil offline?: Yes: Tamil is in Whisper’s list and large-v2 scored 17.5% word error rate on read FLEURS sentences. A Whisper model scored 78.4% on natural Tamil speech in the IndicVoices paper, so test on real meetings.
Why does Whisper do better on Tamil than on other Indian languages?: The paper names no cause for Tamil, but it finds that error rate tracks training hours closely (a squared correlation of 0.83), and Tamil has 136 hours against 12 for Hindi and 4.3 or less for Telugu, Kannada and Bengali.
Which open models list Tamil?: Qwen3, IndicConformer, IndicTrans2, NLLB-200, Meta MMS, and Sarvam’s smaller models all list Tamil. Meta’s Llama 3.3 and Llama 4 cards do not, and Gemma’s cards say over 140 languages without a list.
How good is offline Tamil translation?: IndicTrans2 scored 39.1 chrF++ from English to Tamil and 45.8 from Tamil to English on conversational sentences, close to NLLB 1.2B distilled at 37.2 and 45.7. The scores are overlap measures, so have a Tamil reader check anything official.

What is not real yet

No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.

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Can offline AI handle Tamil?தமிழ் in speech, text and translation: the Indian language Whisper heard most, and where it still falls short.