Hy4 preview leads overall
Ahead on 7 of 7 benchmarks, averaging 10.5 points higher
Summarised from the 7 benchmarks both models were scored on; details in the charts below.

Hy4 preview
腾讯AI实验室
Updates live with the mode filters below.
Best overall
Hy4 preview · 75.67
Best single
Hy4 preview · GPQA Diamond 92.30
Modality coverage
Hy4 preview · 1 modalities
Head to head
7
Benchmarks
7
Wins
0
Losses
+10.51
Average diff
Benchmark-by-benchmark comparison. Changing the thinking mode or tool filters updates the chart and table below.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Each axis is the mean percentage score of one benchmark domain. It is an average, not a capability rating.
Relative edge: 编程与软件工程 +17.1 / Relative gap: none clear
Relative edge: none clear / Relative gap: 编程与软件工程 -17.1
Method: for each model and benchmark, all scores in the current mode scope are averaged (not the best score), then those benchmark scores are averaged within each domain. Only benchmarks scored on a 0-100 scale by at least two of the selected models count — Elo and rating-scale benchmarks such as Codeforces or Arena are excluded, because averaging a 1500 rating with an 85% accuracy produces a meaningless number. Missing values are not counted as zero, and the averages are unweighted, so domains with harder benchmarks read lower.
Every model and runtime mode, benchmark by benchmark. Values are comparable along a row, not between different benchmarks.
7 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | Hy4 preview | Hy3 |
|---|---|---|
HLE 综合评估 | 55.40Thinking Level · High | Tools | 53.20Thinking Level · High | Tools |
GPQA Diamond 科学与综合推理 | 92.30Thinking Level · High | 90.40Thinking Level · High |
DeepSWE 编程与软件工程 | 64.30Thinking Level · High | Tools | 28.00Thinking Level · High | Tools |
SWE-bench Multilingual 编程与软件工程 | 82.90Thinking Level · High | Tools | 75.80Thinking Level · High | Tools |
SWE-Bench Pro - Public 编程与软件工程 | 65.70Thinking Level · High | Tools | 57.90Thinking Level · High | Tools |
MCP-Atlas AI Agent - 工具使用 | 83.70Thinking Level · High | Tools | 79.10Thinking Level · High | Tools |
Terminal-Bench 2.1 AI Agent - 工具使用 | 85.40Thinking Level · High | Tools | 71.70Thinking Level · High | Tools |
Official list prices per model API, split by input and output. Unit: USD per 1M tokens.
Architecture, licensing and API modalities. "Not provided" means the field is missing from our database.
| Features & specs | Hy4 preview腾讯AI实验室 | Hy3腾讯AI实验室 |
|---|---|---|
Core specsRelease | 2026-08-28 | 2026-07-06 |
Context length | 1M | 256K |
Total parameters | 770B | 295B |
Active parameters | 49B | 21B |
Architecture | MoE (mixture of experts) | MoE (mixture of experts) |
Runtime modes | 高关闭 | 关闭低高 |
LicenseCode Open Source | Open Source · Apache 2.0 | Open Source · Apache 2.0 |
Weights Open Source | Open Source · Apache 2.0 | Open Source · Apache 2.0 |
Licensing status | 免费商用授权 | 免费商用授权 |
Local deploymentWeight size | ≈1.42 TiB (BF16, 131 safetensors shards) | Not provided |
VRAM for weights | ≈ 1454 GB (weights only, excludes KV cache) | Not provided |
Weights | Hugging Face | Hugging Face |
Source repo | GitHub | GitHub |
API modality supportText Input/Output | / | / |
ResourcesPaper / report | Introducing Hy4 preview | Hy3 |

Hy3
腾讯AI实验室