TencentbalancedTool use

Hy3 preview (free)

Hy3 Preview is a high-efficiency Mixture-of-Experts model from Tencent designed for agentic workflows and production use. It supports configurable reasoning levels across disabled, low, and high modes, allowing it to...

262K context·~197K words·262K max output

View context details Compare with Amazon Titan Text Express

Context window262Ktokens

Max output262Ktokens

Context window

This model accepts 262K tokens in one request (~197K words of text).

Context window size262K tokens

4K32K128K1M10M

What fits in one request

Short document
About 1,500 words of text
Fits
Long document
About 37K words of text
Fits
Small codebase
About 150K words of text
Fits
Full novel
About 375K words of text
Won't fit

Specifications

Context size, pricing, and release info in one place.

Context window: 262,144 tokens (262K)
Max output tokens: 262,144 tokens (262K)
Speed tier: balanced
Provider: Tencent
Release date: Apr 2026

Capabilities

See which features this model supports, such as vision, tools, and streaming.

Supported (4)

Tool use: Can call external tools and APIs; Supported
Function calling: Structured function call interface; Supported
Extended thinking: Shows its chain-of-thought reasoning; Supported
Streaming: Returns tokens as they are generated; Supported

Not supported (4)

Vision: Accepts image inputs alongside text; Not supported
Web search: Can browse the web during a request; Not supported
Batch API: Process many requests asynchronously; Not supported
Prompt caching: Reuse repeated prompt prefixes cheaply; Not supported

Best for

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Reasoning AI agents Long documents RAG

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Frequently asked questions

Short answers about context size and how this model behaves.

Hy3 preview (free) has a context window of 262K tokens (262,144 tokens). This large window is well-suited for long document analysis, extensive codebases, and multi-session agent workflows.

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Use a smaller model.
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Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

Calculate your savings Learn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent

Full history

Repeated info

Old context

With Mem0~20K tokens sent

Key memories

Current turn

80% less to send — works with any model