The State of Translation Automation 2026 · Languages

English to Afrikaans AI translation quality, cost and speed

What it takes to automate translation from English into Afrikaans against 10 requirements in three levels: the solutions that meet them, what they cost and how fast they are, from the 2026 benchmark of 57 AI models and MT engines.

How good is AI translation from English to Afrikaans?

Key findings on English to Afrikaans translation

  1. 1BottleneckWithin general translation quality, the weighted errors are the bottleneck. The one-step solutions on OpenAI GPT-5.5, OpenAI GPT-5.6 Terra and Anthropic Claude Fable 5 meet the bars for critical and major errors, but have 28.7, 30.3 and 32.0 weighted errors per 1,000 words, above the bar.See the data →
  2. 2Near missThe three-step solutions (translation + LQA + repair) on OpenAI GPT-5.5 and OpenAI GPT-5.6 Terra come close to meeting general translation quality. They have 20.8 and 21.8 weighted errors per 1,000 words, just over the bar, with no critical error and two and three major errors.See the data →
  3. 3Cost driverThe steps and the gender-neutrality agent drive the cost. A solution on Anthropic Claude Fable 5 costs $27.96 per million characters with one step, $562 with three, and $968 with three and the gender-neutrality agent.See the data →

Find English to Afrikaans 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 Afrikaans, 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 13 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. 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

Trade-offs in English to Afrikaans translation

Constraints

For the requirements of every level, Optimize for selects the same solution for quality, cost and latency: the three-step solution (translation + LQA + repair) on Anthropic Claude Fable 5, with the gender-neutrality agent for the Advanced requirements. A limit of one or two steps leaves solutions with at least 28.7 weighted errors per 1,000 words, on OpenAI GPT-5.5 with one step. A real-time limit (<2 sec) leaves three shortlisted solutions, and the one on Translated Lara 2 has the fewest total errors, 51.2 per 1,000 words.

Trade-off

Three three-step solutions on other models cost less and take less time, but have more weighted errors. Against the solution on Anthropic Claude Fable 5, the one on OpenAI GPT-5.6 Terra costs $492 instead of $562 per million characters and takes 152 instead of 203 seconds per 1,000 words. But it has more total errors, 21.8 instead of 19.1 per 1,000 words, with three major errors instead of none and weighted errors above the bar.

Agent effect

For the Advanced requirements, the gender-neutrality agent raises the cost of the three-step solution on Anthropic Claude Fable 5 from $562 to $968 per million characters. The time stays at 203 seconds per 1,000 words. Total errors rise from 19.1 to 19.4 per 1,000 words. Weighted errors rise from 18.8 to 19.4 per 1,000 words and major errors from none to one, both within the bars of general translation quality.

English to Afrikaans translation quality levels

Optimize for
Basic requirements☆

Tier 3: one solution

Solutions that meet them
1 (0 one-step)
Simplest solution
three-step
Fewest errors

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Lowest cost

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Shortest time

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Standard requirements☆

Tier 3: one solution

Solutions that meet them
1 (0 one-step)
Simplest solution
three-step
Fewest errors

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Lowest cost

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Shortest time

Anthropic Claude Fable 5
three-step

Total errors per 1,000 words
19.1
Cost per million characters
$562
Seconds per 1,000 words
203
Advanced requirements☆

Tier 3: one solution

Solutions that meet them
1 (0 one-step)
Simplest solution
with the gender-neutrality agent
Fewest errors

Anthropic Claude Fable 5
three-step with the gender-neutrality agent

Total errors per 1,000 words
19.4
Cost per million characters
$968
Seconds per 1,000 words
203
Lowest cost

Anthropic Claude Fable 5
three-step with the gender-neutrality agent

Total errors per 1,000 words
19.4
Cost per million characters
$968
Seconds per 1,000 words
203
Shortest time

Anthropic Claude Fable 5
three-step with the gender-neutrality agent

Total errors per 1,000 words
19.4
Cost per million characters
$968
Seconds per 1,000 words
203

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.

Quality levelTierSolutionsSimplest solutionModelTotal errors per 1,000 wordsCost per million charactersSeconds per 1,000 words
BasicTier 3: one solution☆three-stepAnthropic Claude Fable 519.1$562203
StandardTier 3: one solution☆three-stepAnthropic Claude Fable 519.1$562203
AdvancedTier 3: one solution☆with the gender-neutrality agentAnthropic Claude Fable 519.4$968203

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.

Level step-up

The step up from Basic to Standard keeps the one solution that meets the Basic requirements, as its translations have 100% of the sentences in the tone of voice and 100% of the tags in place. Terminology does not apply, as there is no glossary for Afrikaans. The step up to Advanced adds the gender-neutrality agent, and the solution with the gender-neutrality agent makes 100% of the sentences about people gender-neutral. The solution has 19.1 total errors per 1,000 words for the Basic and Standard requirements, and 19.4 with the agent.

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

English to Afrikaans translation cost against errors

Chart data
Cost and weighted errors of the one-step solutions in Afrikaans
ModelUS dollars per million charactersWeighted errors per 1,000 wordsGroup
Google Gemma 40.1363.9Misses a Standard requirement
xAI Grok 4.20 (reasoning)1.0949.8Misses a Standard requirement
MoonshotAI Kimi K2.51.2164.9Misses a Standard requirement
Anthropic Claude Haiku 4.52.15132.5Misses a Standard requirement
Google Gemini 3.5 Flash3.3135.3Misses a Standard requirement
OpenAI GPT-5.6 Terra4.1130.3Misses a Standard requirement
Anthropic Claude Sonnet 55.6256Misses a Standard requirement
Anthropic Claude Sonnet 4.66.4940.2Misses a Standard requirement
Microsoft Translator1063.6Misses a Standard requirement
OpenAI GPT-5.510.2528.7Misses a Standard requirement
Translated Lara 224.9950.1Misses a Standard requirement
DeepL Next Gen27.564.3Misses a Standard requirement
Anthropic Claude Fable 527.9632Misses a Standard requirement
Price vs quality

The dearest one-step solutions have more weighted errors than several cheaper ones. The three dearest, on Anthropic Claude Fable 5, DeepL Next Gen and Translated Lara 2, cost $27.96, $27.50 and $24.99 per million characters and have 32.0, 64.3 and 50.1 weighted errors per 1,000 words. The one on OpenAI GPT-5.6 Terra costs $4.11 per million characters and has 30.3 weighted errors per 1,000 words. The one on OpenAI GPT-5.5 has the fewest, 28.7 weighted errors per 1,000 words, at $10.25 per million characters.

How we measure it: 11-01 · 10-10

English to Afrikaans translation requirements

Chart data
Errors per 1,000 words of the one-step solutions in Afrikaans, median, by requirement
RequirementMedian errors per 1,000 words
General translation quality50.1
Tone of voice2.2
Tag handling0.7
Gender neutrality0

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

Bottleneck

Weighted errors are where most solutions fall short in general translation quality. A solution on Anthropic Claude Fable 5 has 32.0 weighted errors per 1,000 words with one step, 31.3 with two and 18.8 with three, under the bar. The other seven three-step solutions have 20.8 to 50.4 weighted errors per 1,000 words. Tags come close on two one-step solutions: translations from Translated Lara 2 have 99.8% of the tags in place and those from OpenAI GPT-5.5 99.6%.

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

AI models and MT engines for English to Afrikaans translation

Chart data
Weighted errors per 1,000 words of the shortlisted one-step solutions in Afrikaans
ModelWeighted errors per 1,000 words of the shortlisted one-step solutions in AfrikaansClass
Anthropic Claude Haiku 4.5132.5LLMs
MoonshotAI Kimi K2.564.9LLMs
DeepL Next Gen64.3LLM-based MT engines
Google Gemma 463.9Open-weight LLMs
Microsoft Translator63.6MT engines
Anthropic Claude Sonnet 556LLMs
Translated Lara 250.1LLM-based MT engines
xAI Grok 4.20 (reasoning)49.8LLMs
Anthropic Claude Sonnet 4.640.2LLMs
Google Gemini 3.5 Flash35.3LLMs
Anthropic Claude Fable 532LLMs
OpenAI GPT-5.6 Terra30.3LLMs
OpenAI GPT-5.528.7LLMs
Model types

The six one-step solutions with the fewest weighted errors are all on LLMs, from 28.7 to 49.8 per 1,000 words, and all six meet our language-support criteria. Translations from the best MT engine, the LLM-based Translated Lara 2, have 50.1 weighted errors per 1,000 words. The two off-the-shelf solutions, on Microsoft Translator and DeepL Next Gen, have 8.5% and 12.77% of the sentences in the tone of voice. The adjusted ones, on Translated Lara 2 and every LLM on the shortlist, have 97.9% to 100% of the sentences in the tone of voice.

How we measure it: 00-04 · 08-15 · 23-01

How we shortlisted English to Afrikaans translation solutions

Chart data
Ranks of the models on the two automatic metrics, Afrikaans
ModelCOMET-KiwiRank on COMET-KiwiMetricXRank on MetricXShortlistedShortlist place
Anthropic Claude Opus 4.80.747111.5112NoNot shortlisted
z.ai GLM-50.746131.4911NoNot shortlisted
Mistral Large 30.746141.489NoNot shortlisted
OpenAI GPT-4.10.745161.5213NoNot shortlisted
Google Gemini 3.1 Pro Preview0.744181.5615NoNot shortlisted
DeepSeek V3.20.743191.5819NoNot shortlisted
OpenAI gpt-oss-120b0.743201.5921NoNot shortlisted
Cohere Command A Translate0.741211.5617NoNot shortlisted
ALL-Lab0.740221.5920NoNot shortlisted
Google Translation LLM0.738232.0628NoNot shortlisted
AI21 Jamba Large 1.70.736241.8427NoNot shortlisted
Alibaba Qwen3-235B-A22B0.736251.6123NoNot shortlisted
Mistral Medium 3.10.729261.8326NoNot shortlisted
MiniMax M2.50.728271.6724NoNot shortlisted
ModernMT Enterprise Edition0.725281.7425NoNot shortlisted
Swiss AI Apertus-8B-25090.723292.0629NoNot shortlisted
Google Cloud Advanced Translation API0.721302.4131NoNot shortlisted
Yandex Cloud Translate v20.709312.3330NoNot shortlisted
Amazon Translate0.693322.6132NoNot shortlisted
AppTek NMT0.666333.3933NoNot shortlisted
Alibaba Machine Translation API0.637343.4034NoNot shortlisted
OpenAI GPT-5.6 Terra0.75311.291YesTop 8 by both metrics
Anthropic Claude Haiku 4.50.75221.5718YesTop 8 by COMET-Kiwi
xAI Grok 4.20 (reasoning)0.75231.426YesTop 8 by both metrics
DeepL Next Gen0.75141.424YesTop 8 by both metrics
Google Gemma 40.75051.478YesTop 8 by both metrics
Anthropic Claude Sonnet 50.75061.4810YesTop 8 by COMET-Kiwi
Translated Lara 20.75071.6022YesTop 8 by COMET-Kiwi
Anthropic Claude Fable 50.74981.5514YesTop 8 by COMET-Kiwi
Microsoft Translator0.74891.5616YesReal-time place
OpenAI GPT-5.50.748101.413YesTop 8 by MetricX
Anthropic Claude Sonnet 4.60.747121.425YesTop 8 by MetricX
Google Gemini 3.5 Flash0.745151.332YesTop 8 by MetricX
MoonshotAI Kimi K2.50.744171.457YesTop 8 by MetricX
ModelSolution complexityCOMET-Kiwi rankCOMET-KiwiMetricX rankMetricXShortlist
OpenAI GPT-5.6 TerraAdjusted LLM10.75311.29Top 8 by both metrics
Anthropic Claude Haiku 4.5Adjusted LLM20.752181.57Top 8 by COMET-Kiwi
xAI Grok 4.20 (reasoning)Adjusted LLM30.75261.42Top 8 by both metrics
DeepL Next GenOff-the-shelf NMT40.75141.42Top 8 by both metrics
Google Gemma 4Adjusted LLM50.75081.47Top 8 by both metrics
Anthropic Claude Sonnet 5Adjusted LLM60.750101.48Top 8 by COMET-Kiwi
Translated Lara 2Adjusted NMT70.750221.60Top 8 by COMET-Kiwi
Anthropic Claude Fable 5Adjusted LLM80.749141.55Top 8 by COMET-Kiwi
Microsoft TranslatorOff-the-shelf NMT90.748161.56Real-time place
OpenAI GPT-5.5Adjusted LLM100.74831.41Top 8 by MetricX
Anthropic Claude Opus 4.8Adjusted LLM110.747121.51Not shortlisted
Anthropic Claude Sonnet 4.6Adjusted LLM120.74751.42Top 8 by MetricX
z.ai GLM-5Adjusted LLM130.746111.49Not shortlisted
Mistral Large 3Adjusted LLM140.74691.48Not shortlisted
Google Gemini 3.5 FlashAdjusted LLM150.74521.33Top 8 by MetricX
OpenAI GPT-4.1Adjusted LLM160.745131.52Not shortlisted
MoonshotAI Kimi K2.5Adjusted LLM170.74471.45Top 8 by MetricX
Google Gemini 3.1 Pro PreviewAdjusted LLM180.744151.56Not shortlisted
DeepSeek V3.2Adjusted LLM190.743191.58Not shortlisted
OpenAI gpt-oss-120bAdjusted LLM200.743211.59Not shortlisted
Cohere Command A TranslateAdjusted LLM210.741171.56Not shortlisted
ALL-LabOff-the-shelf NMT220.740201.59Not shortlisted
Google Translation LLMAdjusted NMT230.738282.06Not shortlisted
AI21 Jamba Large 1.7Adjusted LLM240.736271.84Not shortlisted
Alibaba Qwen3-235B-A22BAdjusted LLM250.736231.61Not shortlisted
Mistral Medium 3.1Adjusted LLM260.729261.83Not shortlisted
MiniMax M2.5Adjusted LLM270.728241.67Not shortlisted
ModernMT Enterprise EditionOff-the-shelf NMT280.725251.74Not shortlisted
Swiss AI Apertus-8B-2509Adjusted LLM290.723292.06Not shortlisted
Google Cloud Advanced Translation APIOff-the-shelf NMT300.721312.41Not shortlisted
Yandex Cloud Translate v2Off-the-shelf NMT310.709302.33Not shortlisted
Amazon TranslateOff-the-shelf NMT320.693322.61Not shortlisted
AppTek NMTOff-the-shelf NMT330.666333.39Not shortlisted
Alibaba Machine Translation APIOff-the-shelf NMT340.637343.40Not shortlisted
OpenAI GPT-5.6 LunaAdjusted LLM—0.751—1.35Same model family as OpenAI GPT-5.6 Terra
OpenAI GPT-5.6 SolAdjusted LLM—0.751—1.51Same model family as OpenAI GPT-5.6 Terra
xAI Grok 4.20 (non-reasoning)Adjusted LLM—0.736—1.57Same model family as xAI Grok 4.20 (reasoning)

Every model we got a translation from, as the shortlist compared it: off the shelf, without context in the request, or adjusted, with it. A model that did not make the shortlist is shown adjusted, unless off the shelf it scores higher by 0.03 or more on COMET-Kiwi. Ranks among 34 models, with each model family counted once, and the top 8 of each metric in bold. Higher is better on COMET-Kiwi, lower on MetricX. The scores rank models within this language and are not a requirement result.

Metrics vs LQA

Translations from Anthropic Claude Haiku 4.5, second on COMET-Kiwi, have 132.5 weighted errors per 1,000 words, the most of the 13 shortlisted solutions. The fewest, 28.7 weighted errors per 1,000 words, come from OpenAI GPT-5.5, on the list through MetricX alone. Anthropic Claude Fable 5, the model of the solutions that meet the levels, is 8th on COMET-Kiwi, the last place in the top 8. The tail models nearest the cut are Mistral Large 3, 9th on MetricX, and Anthropic Claude Opus 4.8, 11th on COMET-Kiwi.

How we measure it: 00-08 · 00-09

English to Afrikaans translation cost

Quality levelCheapest solution that meets every requirement of the levelCost per million characters
BasicAnthropic Claude Fable 5, three-step$562
StandardAnthropic Claude Fable 5, three-step$562
AdvancedAnthropic Claude Fable 5, three-step with the gender-neutrality agent$968
Chart data
Cost of the shortlisted one-step solutions in Afrikaans
ModelUS dollars per million charactersClass
Google Gemma 4$0.13Open-weight LLMs
xAI Grok 4.20 (reasoning)$1.09LLMs
MoonshotAI Kimi K2.5$1.21LLMs
Anthropic Claude Haiku 4.5$2.15LLMs
Google Gemini 3.5 Flash$3.31LLMs
OpenAI GPT-5.6 Terra$4.11LLMs
Anthropic Claude Sonnet 5$5.62LLMs
Anthropic Claude Sonnet 4.6$6.49LLMs
Microsoft Translator$10MT engines
OpenAI GPT-5.5$10.25LLMs
Translated Lara 2$24.99LLM-based MT engines
DeepL Next Gen$27.5LLM-based MT engines
Anthropic Claude Fable 5$27.96LLMs
Chart data
Tokens per character of the translation into Afrikaans, by model
ModelTokens per characterClass
Anthropic Claude Sonnet 50.468LLMs
Anthropic Claude Opus 4.80.467LLMs
Anthropic Claude Fable 50.466LLMs
Mistral Medium 3.10.379LLMs
Mistral Large 30.373LLMs
Anthropic Claude Sonnet 4.60.366LLMs
Anthropic Claude Haiku 4.50.361LLMs
AI21 Jamba Large 1.70.343LLMs
Alibaba Qwen3-235B-A22B0.337Open-weight LLMs
MoonshotAI Kimi K2.50.337LLMs
DeepSeek V3.20.327LLMs
z.ai GLM-50.324LLMs
Cohere Command A Translate0.314LLMs
Google Gemini 3.1 Pro Preview0.309LLMs
Google Gemini 3.5 Flash0.309LLMs
Google Gemma 40.307Open-weight LLMs
MiniMax M2.50.301LLMs
xAI Grok 4.20 (non-reasoning)0.298LLMs
xAI Grok 4.20 (reasoning)0.298LLMs
OpenAI GPT-4.10.288LLMs
OpenAI GPT-5.50.288LLMs
OpenAI GPT-5.6 Terra0.288LLMs
OpenAI GPT-5.6 Luna0.287LLMs
OpenAI GPT-5.6 Sol0.286LLMs
Cost driver

A character of Afrikaans comes to a median 0.32 tokens across the tokenizers of 24 models, 1.3 times the figure for English. The three-step solutions cost $492 to $629 per million characters, against $0.13 to $27.96 for the one-step solutions. Meeting the Basic and Standard requirements costs the same, $562 per million characters, as one solution meets both. Meeting the Advanced requirements costs $968 per million characters, with the gender-neutrality agent.

How we measure it: 10-01 · 10-03 · 05-02

English to Afrikaans translation speed

Quality levelFastest solution that meets every requirement of the levelSeconds per 1,000 words
BasicAnthropic Claude Fable 5, three-step203
StandardAnthropic Claude Fable 5, three-step203
AdvancedAnthropic Claude Fable 5, three-step with the gender-neutrality agent203
Chart data
Time to translate 1,000 words into Afrikaans, by model
ModelSeconds per 1,000 wordsClass
Google Cloud Advanced Translation API0.1MT engines
Microsoft Translator0.2MT engines
ModernMT Enterprise Edition0.4MT engines
Google Translation LLM0.5LLM-based MT engines
DeepL Next Gen0.7LLM-based MT engines
Amazon Translate1.2MT engines
Translated Lara 21.3LLM-based MT engines
OpenAI gpt-oss-120b1.8Open-weight LLMs
Yandex Cloud Translate v23.6MT engines
OpenAI GPT-5.6 Luna14LLMs
xAI Grok 4.20 (non-reasoning)19LLMs
OpenAI GPT-4.123LLMs
Alibaba Machine Translation API26MT engines
OpenAI GPT-5.6 Terra28LLMs
ALL-Lab28MT engines
Anthropic Claude Haiku 4.536LLMs
Mistral Medium 3.137LLMs
MiniMax M2.540LLMs
AI21 Jamba Large 1.746LLMs
Cohere Command A Translate47LLMs
xAI Grok 4.20 (reasoning)53LLMs
Mistral Large 353LLMs
Anthropic Claude Sonnet 558LLMs
OpenAI GPT-5.6 Sol62LLMs
Anthropic Claude Fable 563LLMs
DeepSeek V3.266LLMs
Anthropic Claude Sonnet 4.670LLMs
Google Gemini 3.5 Flash70LLMs
Anthropic Claude Opus 4.873LLMs
Google Gemini 3.1 Pro Preview77LLMs
OpenAI GPT-5.582LLMs
Swiss AI Apertus-8B-250985Open-weight LLMs
AppTek NMT126MT engines
Alibaba Qwen3-235B-A22B133Open-weight LLMs
Google Gemma 4161Open-weight LLMs
z.ai GLM-5197LLMs
MoonshotAI Kimi K2.5216LLMs

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 Afrikaans.

Real-time

Seven of the eight real-time models in Afrikaans are MT engines or LLM-based MT engines, and the eighth is the open-weight OpenAI gpt-oss-120b, outside the shortlist. Translations from the three on the shortlist, Microsoft Translator, DeepL Next Gen and Translated Lara 2, have 63.6, 64.3 and 50.1 weighted errors per 1,000 words. None of them meet formatting or tag handling. The solutions that meet the levels take 203 seconds per 1,000 words, with or without the gender-neutrality agent.

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

Tone of voice and gender-neutral English to Afrikaans translation

Tone of voice
Formal register, with u
Gender-neutrality strategy
rephrasing/plural + neutral nouns
Options in the language
generic hy, hy of sy, rephrasing + plural
Default gender
None where the source leaves the gender open
The two best solutionsSolutionSentences about people that are gender-neutralMeets every Advanced requirementCost per million charactersSeconds per 1,000 words
Anthropic Claude Fable 5three-step, with the gender-neutrality agent100%✓$968203
OpenAI GPT-5.6 Terrathree-step100%✗$492152
Analysis

The tone of voice we check in Afrikaans is the formal register, with "u" as the form of address. For gender neutrality we check rephrasing, plural forms and neutral nouns, and we allow no default gender. The other options in the language are generic "hy" and "hy of sy". Both of the two best solutions make 100% of the sentences about people gender-neutral, the one on OpenAI GPT-5.6 Terra without the agent. Its 21.8 weighted errors per 1,000 words are more than general translation quality allows.

How we measure it: 02-05 · 02-06 · 08-11 · 09-18

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

Confidence

Both metric pairs agree above the threshold, and neither result is borderline. The three LQA judges agree on a median of 97.2% of the sentences across the 13 shortlisted solutions. So the metric rankings and the Intento LQA results on this page are well grounded.

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

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