English to Tatar AI translation quality, cost and speed

Find English to Tatar translation solutions for your requirements

Pick a quality level, or your own requirements, bars and constraints, to see the shortlisted solutions that meet them in Tatar, with a column for each requirement you select. Under Optimize for, choose which of them comes first: the one with the fewest total errors, the lowest cost or the shortest time. Click a column heading to sort by it.

The shortlisted solutions on 11 models, with their Intento LQA results. Total errors per 1,000 words add the weighted general translation quality errors (minor 1, major 5, critical 10) to the missed glossary terms, sentences in the wrong register, tag errors and sentences that fail gender neutrality, each counted once. Formatting counts as met or missed and does not add to the total errors. The models that did not make the shortlist have automatic scores only: the shortlist. Inconclusive: the three LQA judges agree on fewer than 90% of the sentences of the solution, so it has no general translation quality result (09-02). Gender neutrality: the Advanced requirements count the two best solutions of the language, with the gender-neutrality agent where they need it. The results of the other solutions are shown for information.

How we measure it: 11-01 · 11-02

English to Tatar translation quality levels

• A solution meets general translation quality with no critical error, at most three major errors and at most 20 weighted errors per 1,000 words.

Optimize for selects one of the solutions that meet the level: the one with the fewest total errors, the lowest cost or the shortest time. Where no solution meets the level, the card shows the available solution with the fewest total errors and what it misses. Total errors count every requirement with countable errors.

One solution per level: the simplest that meets the level, the cheapest of them where several are equally simple. ★ a one-step solution, ☆ a solution with more steps or the gender-neutrality agent.

How we measure it: 11-01 · 11-02 · 08-09

English to Tatar translation requirements

• Of the 8 shortlisted one-step solutions with a conclusive Intento LQA result, all 8 meet tone of voice, 3 formatting and 2 tag handling.
• None of them meet general translation quality.
• With one-step solutions alone, Tatar is in tier 4 (no solution) for the Standard requirements, with two-step solutions (translation + post-edit) in tier 4 (no solution), and with three-step solutions (translation + LQA + repair) in tier 2 (two or more solutions, none simple).

The requirements with countable errors. Every solution with its result on each requirement: the explorer.

How we measure it: 09-09 · 09-10 · 09-11 · 09-12 · 09-18

How we shortlisted English to Tatar translation solutions

• We shortlisted 11 solutions for Tatar: the top 10 by the similarity score, and 1 added as a real-time solution (<2 sec).
• No quality metric scores Tatar, so we rank the solutions by semantic similarity alone (LaBSE and Cohere embed v3), which does not measure fluency.
• The other 16 models we got a translation from did not make the shortlist: they have automatic scores but no Intento LQA result.
• OpenAI GPT-5.6 Sol and OpenAI GPT-5.6 Terra count once with OpenAI GPT-5.6 Luna, and xAI Grok 4.20 (non-reasoning) with xAI Grok 4.20 (reasoning), as models of one family.
• The similarity score ranks OpenAI GPT-5.5 first in Tatar.

Every model we got a translation from, as the shortlist compared it: off the shelf, without context in the request, or adjusted, with it. Ranks among 27 models, with each model family counted once, and the top 10 in bold. The similarity rank combines LaBSE and Cohere embed v3, higher is better on both. The scores rank models within this language and are not a requirement result.

How we measure it: 00-08 · 00-09

English to Tatar translation speed

• Translations into Tatar are real-time (<2 sec) from 6 models.
• None of the real-time solutions meet every Standard requirement.

Real-time models are those the shortlist counts as real-time, under 2 seconds per text across the languages we timed. The chart shows the time of each model into Tatar.

How we measure it: 12-01 · 12-02 · 12-09

How confident are we in measuring English to Tatar translation quality?

• The similarity pair of automatic metrics agrees in Tatar. The quality-estimation pair cannot be applied, because we have no COMET-Kiwi or MetricX scores in Tatar.
• The three LQA judges agree on 90% or more of the sentences for 8 of the 11 shortlisted solutions.

How we measure it: 00-07 · 07-05 · 09-02