See key specs and per-benchmark scores for each model/mode. Scroll horizontally for all columns. 当前对比 2 个模型的评测数据与核心参数。

DeepSeek-V4-Pro
DeepSeek-AI
Each axis is a category average, normalized to a 100-point radar.
Relative edge: AI Agent - 信息收集 +30.5 / Relative gap: none clear
Relative edge: none clear / Relative gap: AI Agent - 信息收集 -30.5
Method: for each model and benchmark, the chart first averages all scores in the current mode scope instead of taking the best score, then averages those benchmark scores within each category. Only benchmarks with at least two selected models scored are included; missing values are not counted as zero.
Best overall
DeepSeek-V4-Pro · 465.64
Best single
DeepSeek-V4-Pro · CodeForces 3206.00
Modality coverage
DeepSeek-V4-Pro · 2 modalities
Head to head
8
Benchmarks
8
Wins
0
Losses
+117.06
Average diff
Compare benchmark results across thinking modes and tool usage.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Complete scores for each model/mode across selected benchmarks.
8 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | DeepSeek-V4-Pro | DeepSeek V3.2 |
|---|---|---|
GPQA Diamond 综合评估 | 90.10Thinking Level · High | 82.40Thinking Enabled |
HLE 综合评估 | 48.20Thinking Level · Extra High | Tools | 25.10Thinking Enabled |
CodeForces 编程与软件工程 | 3206.00Thinking Level · High | 2386.00Thinking Enabled |
LiveCodeBench 编程与软件工程 | 93.50Thinking Level · High | 83.30Thinking Enabled |
SWE-Bench Pro - Public 编程与软件工程 | 55.40Thinking Level · Extra High | Tools | 40.90Thinking Enabled |
SWE-bench Verified 编程与软件工程 | 80.60Thinking Level · Extra High | Tools | 73.10Thinking Enabled | Tools |
BrowseComp AI Agent - 信息收集 | 83.40Thinking Level · Extra High | Tools | 51.40Thinking Enabled |
Terminal Bench 2.0 AI Agent - 工具使用 | 67.90Thinking Level · Extra High | Tools | 46.40Thinking Enabled | Tools |
Side-by-side input/output token pricing
Licensing, MoE architecture, and multi-modality support.
| Features & specs | DeepSeek-V4-ProDeepSeek-AI | DeepSeek V3.2DeepSeek-AI |
|---|---|---|
Core specsRelease | 2026-04-24 | 2025-12-01 |
Context length | 1M | 128K |
Parameters | 16000 | 6710 |
Active parameters | 490 | 370 |
Max output | 384000 | 8192 |
MoE | Yes | Yes |
LicenseCode Open Source | Closed Source | Not provided |
Weights Open Source | Closed Source | Not provided |
Commercial use | 免费商用授权 | 免费商用授权 |
Modality supportText Input/Output | / | / |
Image Input/Output | / | Not provided |
ResourcesPaper / report | DeepSeek-V4 Technical Report | DeepSeek-V3.2 正式版发布与说明 |
DataLearner blog | Not provided | 复杂问题推理能力大幅提升,DeepSeekAI发布DeepSeek V3.2正式版本以及一个评测结果可以媲美Gemini 3.0 Pro的将开源模型推到极限性能的DeepSeek-V3.2-Speciale模型 |

DeepSeek V3.2
DeepSeek-AI