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

GLM-5.2
智谱AI
Each axis is a category average, normalized to a 100-point radar.
Relative edge: 编程与软件工程 +7.7 / Relative gap: 数学推理 -20.2
Relative edge: 数学推理 +20.2 / Relative gap: 编程与软件工程 -7.7
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
GLM-5.2 · 63.37
Best single
GLM-5.2 · GPQA Diamond 91.86
Modality coverage
DeepSeek-V4-Pro · 1 modalities
Head to head
11
Benchmarks
4
Wins
7
Losses
-1.73
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.
11 benchmarks with comparable scores. Each model shows its best score; mode label is displayed below.
| Benchmark | DeepSeek-V4-Pro | GLM-5.2 |
|---|---|---|
HLE 综合评估 | 48.20Thinking Level · Extra High | Tools | 54.70Thinking Enabled | Tools |
LiveBench 综合评估 | 73.58Standard Mode | 76.24Standard Mode |
GPQA Diamond 科学与综合推理 | 90.10Thinking Level · High | 91.86Thinking Level · High |
DeepSWE 编程与软件工程 | 62.70Thinking Level · Extra High | Tools | 44.00Deep Thinking Mode | Tools |
NL2Repo-Bench 编程与软件工程 | 61.50Thinking Level · Extra High | Tools | 48.90Thinking Enabled | Tools |
SWE-Bench Pro - Public 编程与软件工程 | 55.40Thinking Level · Extra High | Tools | 62.10Thinking Enabled | Tools |
SimpleBench 常识推理 | 61.20Standard Mode | 58.80Standard Mode |
Terminal-Bench 2.1 AI Agent - 工具使用 | 87.90Thinking Level · Extra High | Tools | 81.00Thinking Level · High | Tools |
2.44Thinking Level · High | 29.27Thinking Level · High | |
FrontierMath v2 数学推理 | 45.26Thinking Level · High | 59.21Thinking Level · High |
IMO-AnswerBench 数学推理 | 89.80Thinking Level · High | 91.00Thinking Enabled |
Side-by-side input/output token pricing
Licensing, MoE architecture, and multi-modality support.
| Features & specs | DeepSeek-V4-ProDeepSeek-AI | GLM-5.2智谱AI |
|---|---|---|
Core specsRelease | 2026-08-13 | 2026-06-13 |
Context length | 1M | 1M |
Parameters | 16000 | 7533.3 |
Active parameters | 490 | 400 |
Max output | 384000 | 128000 |
MoE | Yes | Yes |
LicenseCode Open Source | Closed Source | Closed Source |
Weights Open Source | Closed Source | Closed Source |
Commercial use | 免费商用授权 | 免费商用授权 |
Modality supportText Input/Output | / | / |
ResourcesPaper / report | DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence | GLM-5: from Vibe Coding to Agentic Engineering |