Hy-MT2-1.8B

Hy-MT2-1.8B

Quick answer: Hy-MT2-1.8B is the lightweight member of Tencent Hunyuan's Hy-MT2 family — a 1.8B-parameter, Apache 2.0-licensed multilingual translation-specialist model supporting 33 languages. It scores 79.77 (XCOMET-XXL) on FLORES-200's full translation matrix and 50.30 on WMT25, and — despite its small size — outperforms commercial translation APIs from Microsoft and Doubao overall. With AngelSlim's 1.25-bit quantization it needs only ~440MB of storage, making it well suited for on-device deployment.

At a Glance

Where Hy-MT2-1.8B leads

• Outperforms Tower-Plus-72B (a much larger open translation-specialist model) and is competitive with Microsoft Translator and Doubao Translator across FLORES-200, WMT25, and domain/real-world translation benchmarks
• Extreme on-device efficiency: AngelSlim 1.25-bit quantization shrinks storage to ~440MB with a 1.5x inference speedup over the prior generation's 4-bit build
• Supports 33 languages including several minority/low-resource Mandarin-adjacent language pairs

Where it lags

• Clearly behind its own larger siblings (Hy-MT2-7B, Hy-MT2-30B-A3B) on every reported benchmark, and behind frontier general-purpose models like Gemini 3.1 Pro on raw translation quality
• General instruction-following (IFBench, IFEval, MaXIFE, Multi-IF) is notably weaker than translation-specific instruction following — it's tuned for translation tasks, not general-purpose chat

Best for: On-device or resource-constrained translation deployments (mobile apps, embedded systems, edge inference) where a dedicated small translation model outperforms general-purpose LLMs of similar size.

What Hy-MT2-1.8B Is

Hy-MT2-1.8B is the smallest of three sizes (1.8B, 7B, 30B-A3B) in Tencent Hunyuan's second-generation "fast-thinking" multilingual translation model family, described in the technical report "Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild." It's a dense transformer (32 layers, 2048 hidden size) trained via a three-stage Family-Centric Post-training (FCPT) pipeline: MT-oriented mid-training on ~1T tokens of translation-related data, followed by Reference-Guided On-Policy Distillation and Family-specific RL training organized around language families (Western European, East Asian, Middle Eastern right-to-left), then a final Cross-family distillation step into a unified model.

Unlike general-purpose LLMs that treat translation as one of many capabilities, Hy-MT2-1.8B is purpose-built and evaluated across four dimensions: general translation (FLORES-200, WMT25, Mandarin⇔Minority), real-world business scenarios (Tencent's own WildMTBench), domain-specific translation (Tencent's own DomainMTBench, covering finance/law/medicine/technology/politics/education), and translation instruction-following (IFMTBench, plus general instruction benchmarks IFBench/IFEval/MaXIFE/Multi-IF). It also supports structured translation-instruction prompting — preserving delimiters, following style constraints, translating only specific fields in structured data, and respecting terminology references.

Specifications

Pricing

Open weights under Apache 2.0 — self-hosted via transformers, vLLM, SGLang, or llama.cpp (GGUF builds available, including 2-bit and 1.25-bit AngelSlim-quantized variants for extreme on-device compression). No API list price; cost is your own inference infrastructure.

Public Benchmark Scores

Hy-MT2-1.8B also reports scores on Tencent's own in-house evaluation suites (WildMTBench, DomainMTBench, IFMTBench, Mandarin⇔Minority testset) and on general instruction-following benchmarks (IFBench, IFEval, MaXIFE, Multi-IF) — not added as Benchgen leaderboard entries since these either lack an independent public benchmark page (WildMTBench/DomainMTBench/IFMTBench are Tencent-constructed, non-independently-reproducible test sets) or measure general instruction-following rather than translation capability specifically.

Hy-MT2-1.8B vs Alternatives

Hy-MT2-1.8B trades peak translation quality for deployability — it's meaningfully behind both larger siblings on FLORES-200, but remains the only model in this family (and one of very few models at this parameter scale generally) purpose-built and independently competitive against commercial translation APIs.

Related Models & Benchmarks

• Compare: Hy-MT2-7B · Hy-MT2-30B-A3B
• Benchmarks: FLORES-200 · WMT25

Frequently Asked Questions

Specs from Tencent Hunyuan's official Hy-MT2-1.8B Hugging Face model card and technical report (arXiv:2605.22064). Last updated 2026-08-31.