Languages
/
Yoruba

24.7% fewer tokenson NTREX-128.

Nzinga needs 115,879 tokens for 1,997 NTREX-128 sentences. Aya Expanse, the best other tokenizer, needs 153,841.

Yoruba needs 24.7% fewer tokens than Aya Expanse on NTREX-128, though above the target.
24.7%
fewer on NTREX-128
1.98x
premium
7.8%
FLORES+ saving
0
test sentences overlap the training text

The challenge

Yoruba writes tone marks, and 1,311 of 1,997 NTREX-128 sentences write them as separate characters. With Gemma 3, Yoruba takes 3.17 times the tokens of English.

The change

Nzinga converts input to the standard composed form before splitting, and added 32,000 African word pieces trained on open web text, including 25.0 million characters of Yoruba.

normalize: nfc ntrex-128: nzinga: 115,879 aya-expanse: 153,841 flores+: nzinga: 53,701 · gpt-4o: 58,238

Still the fewest tokens of any tokenizer tested, though above the target.

FLORES+ devtest
,
premium 1.98x
,
Yoruba result

The result

Nzinga needs 24.7% fewer tokens than Aya Expanse on NTREX-128 and 7.8% fewer than GPT-4o on FLORES+. The FLORES+ premium is 1.98 times English, still above the 1.3 to 1.5 target.

Before Nzinga, and after.

Before: Gemma 3 alone
Tokens on NTREX-128 news
Before
167,966
After
115,879
Tokens on FLORES+
Before
65,233
After
53,701
Premium on FLORES+
Before
2.41x
After
1.98x
Closing the gap

Fewer tokens for African-language AI models.

Record in your language. The demo is open.