Best AI models for Turkish

The same text can need a different number of tokens in Turkish than in English, and the gap depends on the model. We measured it ourselves, then combined it with independent quality scores and current prices to show which models give the best results for your money in Turkish.

The same text needs 30% to 103% more tokens in Turkish than in English, depending on the model. Google (Gemma 3) is the most efficient, DeepSeek (V3.1) the least.

The cost of Turkish, by model family

TokenizeriTokens (English)Tokens (Turkish)Extra vs English
Google (Gemma 3)218284
+30%
Meta (Llama 4)219288
+32%
OpenAI (GPT-4o)219296
+35%
Alibaba (Qwen 3)219341
+56%
Mistral (Nemo)220346
+57%
Z.ai (GLM-4.5)219365
+67%
DeepSeek (V3.1)219445
+103%

Anthropic (Claude) and xAI (Grok) do not publish their tokenizers, so they cannot be measured; for their models we use the average of the measured families (marked ≈). Google’s Gemini is estimated with Google’s open Gemma tokenizer.

Most capable models and their real cost in Turkish

Rankings →
ModelOverall indexiTurkish factorInputi1,000 pages
166.6×1.35$10$4.58
165.0≈ ×1.54$10$5.22
163.6≈ ×1.54$10$5.22
Claude Opus 5Anthropic
162.7≈ ×1.54$5$2.61
162.5×1.35$30$13.73
162.0×1.35$2$0.915
159.3×1.35$2$0.915
GPT-5.5OpenAI
159.3×1.35$5$2.29
159.1×1.35$30$13.73
158.3≈ ×1.54$5$2.61
Gemini 3.7 FlashGoogle DeepMind
157.7×1.30$0.75$0.329
Kimi K3Moonshot AI
157.7≈ ×1.54$3$1.57
Gemini 3.8 FlashGoogle DeepMind
157.1×1.30$0.75$0.329
156.9×1.32$1.25$0.557
GPT-5.4OpenAI
156.9×1.35$2.50$1.14

Cost to read 1,000 pages of text (about 300,000 words in English) written in Turkish, as input. Each model gets the factor measured on its company’s latest public tokenizer, so treat it as an estimate: newer models may use a different tokenizer. ≈ marks companies that publish no tokenizer (average of measured families).

Best value for Turkish

Strong models (overall index 140 or more), cheapest first for processing Turkish text.

Tips for using AI in Turkish

  1. Ask for answers in Turkish explicitly, especially when your question contains English terms; otherwise some models switch to English.
  2. Test with your own content. Quality scores are measured mostly in English, so try your finalists on real Turkish examples before you decide.
  3. Compare token costs. Depending on the model, the same content in Turkish costs between +30% and +103% compared with English, and Google (Gemma 3) handles it most efficiently.
  4. Name your audience. Vocabulary, tone and formality vary between regions and situations: tell the model who you are writing for and how formal it should be.
  5. Proofread names, numbers and punctuation. Generated text can be fluent yet get proper names, dates or local conventions wrong, so review anything you publish.

How we measured

We wrote the same four texts (a news item, a customer email, a technical explanation and travel tips) in 15 languages, then counted the tokens that each public tokenizer produces. Quality scores come from Epoch AI and are measured mostly in English, so always test the finalists on your own Turkish content.

Get a personal recommendationCount the tokens of your own text