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Hy-MT2-7B

A model built only for translation, with options for glossaries and writing style. Covers 33 language pairs plus some Chinese dialects.

Last updated October 16, 2026.

Costs here use the prices AI companies charge software developers, so they show relative cost, not your monthly bill. See what ChatGPT, Claude and Gemini charge you.

Made by Tencent. Single-purpose.

What it costs

1,000-word essay: under 1 cent
100 chat messages: $0.10 (about 10 cents)
50-page PDF summary: under 1 cent

Based on list prices and the assumptions on How we work. Your real cost will differ.

At a glance

Smartness: Not rated yet (our banding of the Artificial Analysis score, where available)
Reads at once: about 10 pages (rule of thumb)
Understands: text
Free to download and run yourself: Yes
Free to use: Not free for developers. Free app plans

Best for

translation

Watch out for

Short inputs only, and translation only.

Picked for

Translate

Frequently asked

How much does Hy-MT2-7B cost to use?
A 1,000-word essay costs about under 1 cent; summarizing a 50-page PDF about under 1 cent. These are developer (API) prices, not an app subscription.

What is Hy-MT2-7B best for?
A model built only for translation, with options for glossaries and writing style. Covers 33 language pairs plus some Chinese dialects.

How much can Hy-MT2-7B read at once?
About 10 pages (a rule of thumb: 8,192 tokens at roughly 500 words a page).

Can I download Hy-MT2-7B for free?
Yes, the model files are published, though running a large one needs powerful hardware.

Under the hood

Maker	Tencent
Price per 1M input tokens	$0.074
Price per 1M output tokens	$0.29
Context size	8K tokens (8,192)
Artificial Analysis Intelligence Index	Not reported (source, via OpenRouter)
Open weights	Yes (Hugging Face: tencent/Hy-MT2-7B)
Speed	Not measured yet
Listed	2026-08-19

Maker's description (technical)

Hy-MT2-7B is a 7B-parameter translation model from Tencent. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and style-guided translation.

View on OpenRouter. Our verdict above is editorial, not benchmarked by us.