Hy3 FP8

Name: Hy3 FP8
Author: Tencent

by Tencent

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released July 2026262K context≈ 196,608 words

Hy3 FP8 is Tencent's open-weight text model running in 8-bit floating point precision, which reduces memory footprint compared to full-precision variants while trading some numerical fidelity. It handles an exceptionally large context window of 262,144 tokens, making it capable of processing very long documents in a single pass. Specific capability details beyond its architecture and context capacity are limited.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Exceptional

Reasoning & Logic

Hy3 FP8

by Tencent

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released July 2026262K context≈ 196,608 words

Hy3 FP8 is Tencent's open-weight text model running in 8-bit floating point precision, which reduces memory footprint compared to full-precision variants while trading some numerical fidelity. It handles an exceptionally large context window of 262,144 tokens, making it capable of processing very long documents in a single pass. Specific capability details beyond its architecture and context capacity are limited.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Long Context

Exceptional

Reasoning & Logic

Glossary

ArchitectureThe underlying structural design of a neural network that defines how data flows through layers and components.Context WindowThe maximum number of tokens a model can process in a single conversation or prompt.FidelityThe degree to which a quantized or compressed model preserves the quality and accuracy of the original full-precision model.Floating Point PrecisionThe number of bits used to represent decimal numbers in a model; lower precision (like 8-bit) uses less memory but may lose some accuracy compared to higher precision (like 32-bit).Full-PrecisionA model using standard 32-bit floating-point numbers to represent weights, providing maximum accuracy but requiring more memory.Memory FootprintThe amount of RAM or storage space a model requires to run, which is critical for deployment on resource-constrained devices.Numerical FidelityThe accuracy and precision with which a model preserves mathematical calculations; lower fidelity means some precision is lost, often as a trade-off for smaller model size.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.Text ModelA language model that processes and generates only text, without support for images, audio, or other media types.TokensThe basic units of text that a language model processes, typically representing words or word fragments.

Capabilities

Capabilities

Use Case Fit

Glossary