Hy4 preview leads overall
Ahead on 6 of 11 benchmarks, averaging 1.4 points higher
Summarised from the 11 benchmarks both models were scored on; details in the charts below.

DeepSeek-V4-Pro
DeepSeek-AI
Updates live with the mode filters below.
Best overall
Hy4 preview · 64.75
Best single
Hy4 preview · GPQA Diamond 92.30
Modality coverage
DeepSeek-V4-Pro · 1 modalities
Head to head
11
Benchmarks
4
Wins
6
Losses
-1.40
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: Agent能力评测 +2.9 / Relative gap: 综合评估 -14.8
Relative edge: 综合评估 +14.8 / Relative gap: Agent能力评测 -2.9
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.
11 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | DeepSeek-V4-Pro | Hy4 preview |
|---|---|---|
HLE 综合评估 | 48.20Thinking Level · Extra High | Tools | 55.40Thinking Level · High | Tools |
GPQA Diamond 科学与综合推理 | 90.10Thinking Level · High | 92.30Thinking Level · High |
DeepSWE 编程与软件工程 | 62.70Thinking Level · Extra High | Tools | 64.30Thinking Level · High | Tools |
NL2Repo-Bench 编程与软件工程 | 61.50Thinking Level · Extra High | Tools | 58.90Thinking Level · High | Tools |
SWE-bench Multilingual 编程与软件工程 | 76.20Thinking Level · Extra High | Tools | 82.90Thinking Level · High | Tools |
SWE-Bench Pro - Public 编程与软件工程 | 55.40Thinking Level · Extra High | Tools | 65.70Thinking Level · High | Tools |
AutomationBench AI Agent - 工具使用 | 31.80Thinking Level · Extra High | Tools | 32.10Thinking Level · High | Tools |
CyberGym AI Agent - 工具使用 | 83.30Thinking Level · Extra High | Tools | 78.40Thinking Level · High | Tools |
Terminal-Bench 2.1 AI Agent - 工具使用 | 87.90Thinking Level · Extra High | Tools | 85.40Thinking Level · High | Tools |
Toolathlon-Verified AI Agent - 工具使用 | 74.10Thinking Level · Extra High | Tools | 74.10Thinking Level · High | Tools |
Agents' Last Exam Agent能力评测 | 25.70Thinking Level · Extra High | Tools | 22.80Thinking 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 | DeepSeek-V4-ProDeepSeek-AI | Hy4 preview腾讯AI实验室 |
|---|---|---|
Core specsRelease | 2026-08-13 | 2026-08-28 |
Context length | 1M | 1M |
Total parameters | 1.6T | 770B |
Active parameters | 49B | 49B |
Max output length | 384,000 tokens | Not provided |
Architecture | MoE (mixture of experts) | MoE (mixture of experts) |
Runtime modes | 最高关闭高 | 高关闭 |
LicenseCode Open Source | Open Source · MIT License | Open Source · Apache 2.0 |
Weights Open Source | Open Source · MIT License | Open Source · Apache 2.0 |
Licensing status | 免费商用授权 | 免费商用授权 |
Local deploymentWeight size | Not provided | ≈1.42 TiB (BF16, 131 safetensors shards) |
VRAM for weights | Not provided | ≈ 1454 GB (weights only, excludes KV cache) |
Weights | Hugging Face | Hugging Face |
Source repo | Not provided | GitHub |
API modality supportText Input/Output | / | / |
ResourcesPaper / report | DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence | Introducing Hy4 preview |

Hy4 preview
腾讯AI实验室