Tutor comparison · September 25, 2026

Talio vs. a generic AI tutor

Same AI model, same scenarios, same simulated Mandarin learner. Only the tutor's instructions differ: Talio's, or a generic “friendly language tutor” prompt that knows the learner's level.

8 matched pairs (4 at A2, 4 at B1), 16 exchanges each, both tutors on OpenAI gpt-realtime.

Why simulated learners?

To compare tutors, everything except the tutor has to stay fixed. A simulated learner makes that possible: the same learner, at the same level, meets both tutors in the same scenario. It also lets us test every change to the tutor quickly, across many scenarios and levels. It measures how the tutor behaves; how much students learn is a question for the classroom.

Gets students talking

The generic AI talks. Talio gets the learner talking.

Learners did 72% of the talking with Talio at A2 and 68% at B1, against 50% and 45% with the generic tutor: more of the floor in 8 of 8 matched pairs.

Learner's share of the talking

  • Talio
  • Generic AI tutor
A2: Talio 72%, generic AI tutor 50%. B1: Talio 68%, generic AI tutor 45%. Each figure is the median, across that level's four conversations, of the learner's share of all characters spoken, counted from the transcripts (Mandarin is counted in characters, not words). Higher with Talio in 8 of 8 matched pairs.
LevelTalioGeneric AI tutor
A272%50%
B168%45%

Learner's share of the talking in each matched pair

  • Talio
  • Generic AI tutor
Talio higher in 8 of 8 pairs. Each level figure in the chart above is the median of that level's four pairs shown here.
PairTalioGeneric AI tutor
A2 Hobbies 173%52%
A2 Dining 168%48%
A2 Hobbies 275%55%
A2 Dining 271%47%
B1 Social 167%48%
B1 Taxi 168%41%
B1 Social 272%53%
B1 Taxi 268%38%

Talio opens a conversation. The generic AI opens a lesson.

B1, “Social Invitations”

Talio

Tutor
哎,最近怎么样?有没有什么想一起出去玩的想法?Hey, how have things been? Any ideas for something fun to do together?
Learner
嗨,最近还挺不错的,就是有点忙,不过我很想出去放松一下。你觉得我们可以去附近的一个公园…?你呢,最近你有什么特别想去的地方吗?Hi, things have been pretty good, just a bit busy, but I'd really like to get out and relax. Do you think we could go to a nearby park…? What about you, anywhere you've especially wanted to go lately?
Tutor
我还挺想去那个新开的植物园看看。你觉得怎么样?I've actually been wanting to check out that new botanical garden. What do you think?

Starts the conversation as a friend would. By turn 3 the learner is making plans in their own words.

Generic AI tutor

Tutor
你好!今天咱们来练习怎么邀请别人一起出去,然后讨论时间和地点,最后礼貌地接受或者拒绝。你准备好了吗?Hi! Today we're going to practice how to invite someone out, then discuss the time and place, and finally politely accept or decline. Are you ready?
Learner
好的,我准备好了。我们先来试一下,比如我想问一个朋友:你明天有空吗?…你觉得这样开始可以吗?OK, I'm ready. Let's try it: for example, I'd ask a friend “Are you free tomorrow?”… Do you think that's a good way to start?
Tutor
可以啊,那我们就先来试试。比如,我来扮演你的朋友。你可以对我说:“你明天有空吗?要不要一起去公园?”然后我们就看看怎么继续把对话说下去。准备好的话,你就开始问吧。Sure, let's give it a try. I'll play your friend. You can say to me: “Are you free tomorrow? Want to go to the park together?” Then we'll see how to keep the conversation going. When you're ready, go ahead and ask.

Opens as a teacher describing the exercise. By turn 3 the learner is repeating a sentence the tutor scripted for them.

Responds to what they say

When the learner is confused, Talio says less.

After a learner signals confusion, the generic tutor's next turn grows to 2.5–2.6× its usual length. Talio's shrinks to 0.80–0.83×: lower in 4 of 4 matched pairs, on all 3 tagging runs.

The tutor's next turn after a confusion signal, vs. its usual turn (A2, median)

  • Talio
  • Generic AI tutor
Talio 0.80–0.83×; generic AI tutor 2.5–2.6×. Left of the 1× line the turn got shorter, right of it longer. Talio lower in 4 of 4 matched pairs, on all 3 tagging runs; each range is the spread across runs.
TutorNext turn vs. usual length
Talio0.80–0.83×
Generic AI tutor2.5–2.6×

Talio hears trouble (repeat requests, one-word replies, switching to English) and rephrases just the unclear part. Students can also ask for a hint, slow the pace, or turn on romanization.

A2, “Hobbies & Free Time”

Talio: 0.8×, 0 new questions

Tutor
哎,你这儿也这么巧啊?最近在忙什么呢?Oh, what a coincidence running into you here! What have you been up to lately?
Learner
…呃,你说的“巧”是意思是幸运吗?我不太明白,你可以再说一次吗?…Um, does the “qiǎo” you said mean lucky? I don't quite understand. Could you say it again?
Tutor's next turn
我刚是说“巧”,就是碰巧遇到的意思。I just said “qiǎo”. It means running into someone by chance.

Explains the one word, in one short sentence, then stops.

Generic AI tutor: 1.9× usual length, 5 questions

Tutor
你好!好久不见!最近怎么样?周末有什么打算吗?Hi! Long time no see! How have you been? Any plans for the weekend?
Learner
…呃,你说周末?周末的打算?…你可以慢一点说吗?我、我想听懂。…Um, you said weekend? Weekend plans? …Can you speak a little slower? I-I want to understand.
Tutor's next turn
好的,我慢一点说。我刚才是想问,你这个周末有什么打算?比如,你想不想去公园走走?或者去参加一个活动?还是在家休息?你觉得呢?OK, I'll speak a little slower. What I was asking is, what are your plans this weekend? For example, would you like to go for a walk in the park? Or go to an event? Or rest at home? What do you think?

Promises to slow down, then delivers a longer turn with more questions.

Selection rule, fixed before reading the transcripts: the opening exchanges of the first matched pair run at each level. At A2, the learner's first confusion signal happens to be their first reply. Synthetic Mandarin learner; English glosses ours; learner turns trimmed with “…” for space, tutor turns shown in full.

What Talio adds

What Talio adds to every scenario

The generic tutor gets 322 characters of instructions. Talio's gets about 15,000 in 11 categories, most of it calibrated to the scenario, level or language.

  • Role & character

    Calibrated by scenario

  • Regional persona & accent

    Calibrated by language, level

  • Scenario & goals

    Calibrated by scenario

  • Level calibration

    Calibrated by level

  • Register & address

    Calibrated by relationship, language

  • Turn length

    Calibrated by level

  • Handling trouble

    Same everywhere

  • Language & variety

    Calibrated by language, region

  • Natural conversation

    Calibrated by language, variety

  • Cultural norms

    Calibrated by language

  • Few-shot prompting

    Calibrated by language, variety

  • Guardrails

    Same everywhere

Few-shot examples

TeachesExample (Mandarin)
Turn length (GOOD)哇,爬山啊!听起来不错。
Repair你去哪儿? · 蓝色的? · 啊?
Native reactions真的假的? · 天哪 · 太夸张了
Listening tokens嗯 · 对对对 · 是吧
Never say你的中文说得真好“your Chinese is so good”

The scenario sets role, scene, goals and relationship. The language file sets regional personas, variety, cultural norms, address rules and every few-shot example. The level sets complexity, turn length and accent. Taiwan Mandarin gets its own set in Traditional characters.

Work with us

Two asks: your expertise and your classroom.

  1. Your expertise. Tell us how you would measure, give feedback and validate.
  2. Your classroom. Pilot Talio with a class, ideally as a research site.

What a Talio conversation records, and how a study works: Talio for researchers.