hy-mt2-7b
Hy-MT2-7B is a 7B translation model from Tencent covering 33 language pairs plus five Chinese dialect and minority-language pairs, with workflows for structured, contextual, glossary-based and style-guided translation.
Precio: Entrada: 17.76 créditos / 1 M de tokens (≈ $0.09); salida: 70.8 créditos / 1 M de tokens (≈ $0.35).
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Hy-MT2-7B API on ModelFold
Hy-MT2-7B is a 7B translation model from Tencent covering 33 language pairs plus five Chinese dialect and minority-language pairs, with workflows for structured, contextual, glossary-based and style-guided translation. Try Hy-MT2-7B in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Hy-MT2-7B API
Hy-MT2-7B at a glance
Hy-MT2-7B is a chat model from Tencent. It accepts text as input and returns text, with a context window of up to 8K tokens.
Use it without hosting anything
On ModelFold you call Hy-MT2-7B with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Hy-MT2-7B
Up to 8K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Hy-MT2-7B on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Hy-MT2-7B responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "hy-mt2-7b" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Hy-MT2-7B
Multilingual products
Serve users in many languages with translation, localized support replies and cross-language search.
Writing and content
Draft, edit and translate articles, emails, product copy and documentation in a consistent tone.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Frequently Asked Questions
What is Hy-MT2-7B?⌄
Hy-MT2-7B is a 7B translation model from Tencent covering 33 language pairs plus five Chinese dialect and minority-language pairs, with workflows for structured, contextual, glossary-based and style-guided translation.
Which inputs does Hy-MT2-7B support?⌄
Hy-MT2-7B accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Hy-MT2-7B?⌄
Up to 8K tokens, shared between your input and the model’s output.
Does Hy-MT2-7B support function calling?⌄
Function calling is not listed for Hy-MT2-7B; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Hy-MT2-7B billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Hy-MT2-7B through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "hy-mt2-7b", using your ModelFold API key as the Bearer token.
| Entrada | 17.76 créditos 1M tokens≈ $0.09 |
| Salida | 70.8 créditos 1M tokens≈ $0.35 |
Se cobra por token, con tarifas separadas para entrada y salida. Los tokens de razonamiento cuentan como salida. El entorno de pruebas aplica exactamente el mismo cálculo.
Leer la documentación de la API →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"hy-mt2-7b","messages":[{"role":"user","content":"Hello"}]}'