Tencent Hy Team
Tencent Hy4 preview
Version preview benchmark runs across the shared Superbash visual prompts.
Try the visual runs
Open the generated scene to test it, or compare that prompt with another model.
Helm's Deep
Fortress siege scene testing scale, lighting, architecture, and cinematic atmosphere.
Hogwarts Broom Flight Simulator
Broom-flight scene testing depth, motion cues, castle scale, and fantasy mood.
Jabberwock
Dark fantasy encounter testing creature design, forest mood, and narrative staging.
Low Poly World
Stylized island build testing composition, color, and low-poly worldbuilding.
Office Life
Workplace vignette testing everyday scene logic, objects, and believable office detail.
Petri Dish
Microscopic ecosystem testing organic forms, scientific clarity, and cellular detail.
Universe Simulator
Cosmic system testing orbital structure, glowing bodies, scale, and simulation readability.
Vice City
Neon coastal city testing vehicles, architecture, atmosphere, and dense urban layout.
Yingzao Fashi Assembly
Timber assembly scene testing structure, joinery, construction order, and material clarity.
Official benchmark profile
A blind internal expert comparison, stated in prose; the standard benchmark tables are published as images.
Blind expert side-by-side
2.99 averageFull official benchmark table1 scores and peer comparisons
| Benchmark | Area | Score | Comparison |
|---|---|---|---|
| Blind expert side-by-side | Engineering work | 2.99 average |
Sources, pricing details and methodology
Verified model facts
Model specifications
- Status
- Preview / limited access
- API model ID
hy4-preview- Context
- 1M
- Max output
- Not publicly verified
- License
- Apache-2.0
- Access route
- Self-hosted only; no hosted Hugging Face Inference Provider was listed at check.
- Modalities
- text generation; unknown: image, audio, and video input/output
- Hardware
- Vendor FP8 vLLM/SGLang recipe uses tensor parallelism of 8; minimum GPU/VRAM and cost are not verified.
- API price · USD / 1M tokens
- Not publicly verified
Benchmark sources
Tencent describes Hy4 preview as a 770B-total, 49B-active MoE with a 1M-token context window released under Apache-2.0. It claims gains in software engineering, office and analysis, game development, and scientific research. Every figure below is a Tencent claim measured under Tencent’s own setup, not an independent reproduction.
Hy4 preview model cardTencent publishes the Hy4 preview benchmark tables and appendix as images, so no machine-readable scores exist to restate here. The card also lists no hosted inference route.
Evaluation settings
- 163 internal Tencent experts rated model outputs on 203 engineering tasks, scored out of 3. Against GLM 5.3 the split was 46.8% wins / 12.8% ties / 40.4% losses; against Kimi K3 it was 51.2% wins / 7.9% ties / 40.9% losses. Tencent characterises both margins as slight.