Compare · ModelsLive · 3 picked · head to head
DeepSeek V4 Pro vs GLM 5.2 vs GPT-5.2-Codex
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
GLM 5.2 wins on 6/12 benchmarks
GLM 5.2 wins 6 of 12 shared benchmarks. Leads in coding · knowledge · speed.
Category leads
coding·GLM 5.2reasoning·GPT-5.2-Codexlanguage·GPT-5.2-Codexmath·DeepSeek V4 Proknowledge·GLM 5.2speed·GLM 5.2arena·GLM 5.2
Hype vs Reality
Attention vs performance
DeepSeek V4 Pro
#13 by perf·no signal
GLM 5.2
#11 by perf·no signal
GPT-5.2-Codex
#18 by perf·no signal
Best value
DeepSeek V4 Pro
3.7x better value than GLM 5.2
DeepSeek V4 Pro
112.8 pts/$
$0.65/M
GLM 5.2
30.5 pts/$
$2.50/M
GPT-5.2-Codex
9.0 pts/$
$7.88/M
Vendor risk
Mixed exposure
One or more vendors flagged
DeepSeek
$3.4B·Tier 1
z-ai
private · undisclosed
OpenAI
$840.0B·Tier 1
Head to head
12 benchmarks · 3 models
DeepSeek V4 ProGLM 5.2GPT-5.2-Codex
LiveBench · Agentic Coding
GLM 5.2 leads by +16.7
DeepSeek V4 Pro
56.7
GLM 5.2
73.3
GPT-5.2-Codex
51.7
LiveBench · Coding
GPT-5.2-Codex leads by +4.0
DeepSeek V4 Pro
70.0
GLM 5.2
79.7
GPT-5.2-Codex
83.6
LiveBench · Data Analysis
GPT-5.2-Codex leads by +3.7
DeepSeek V4 Pro
74.5
GLM 5.2
73.7
GPT-5.2-Codex
78.2
LiveBench · If
GPT-5.2-Codex leads by +4.1
DeepSeek V4 Pro
62.4
GLM 5.2
62.3
GPT-5.2-Codex
66.5
LiveBench · Language
DeepSeek V4 Pro leads by +1.9
DeepSeek V4 Pro
78.1
GLM 5.2
76.2
GPT-5.2-Codex
73.7
LiveBench · Mathematics
DeepSeek V4 Pro leads by +0.9
DeepSeek V4 Pro
90.7
GLM 5.2
89.8
GPT-5.2-Codex
88.8
LiveBench · Overall
GLM 5.2 leads by +1.9
DeepSeek V4 Pro
73.6
GLM 5.2
76.2
GPT-5.2-Codex
74.3
LiveBench · Reasoning
DeepSeek V4 Pro leads by +4.1
DeepSeek V4 Pro
82.7
GLM 5.2
78.6
GPT-5.2-Codex
77.7
Artificial Analysis · Agentic Index
GLM 5.2 leads by +6.7
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
DeepSeek V4 Pro
36.4
GLM 5.2
43.1
Artificial Analysis · Coding Index
GLM 5.2 leads by +9.4
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
DeepSeek V4 Pro
59.4
GLM 5.2
68.8
Artificial Analysis · Quality Index
GLM 5.2 leads by +6.8
DeepSeek V4 Pro
44.3
GLM 5.2
51.1
Chatbot Arena Elo · Overall
GLM 5.2 leads by +15.1
DeepSeek V4 Pro
1455.9
GLM 5.2
1471.0
Full benchmark table
| Benchmark | DeepSeek V4 Pro | GLM 5.2 | GPT-5.2-Codex |
|---|---|---|---|
LiveBench · Agentic Coding | 56.7 | 73.3 | 51.7 |
LiveBench · Coding | 70.0 | 79.7 | 83.6 |
LiveBench · Data Analysis | 74.5 | 73.7 | 78.2 |
LiveBench · If | 62.4 | 62.3 | 66.5 |
LiveBench · Language | 78.1 | 76.2 | 73.7 |
LiveBench · Mathematics | 90.7 | 89.8 | 88.8 |
LiveBench · Overall | 73.6 | 76.2 | 74.3 |
LiveBench · Reasoning | 82.7 | 78.6 | 77.7 |
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 36.4 | 43.1 | — |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 59.4 | 68.8 | — |
Artificial Analysis · Quality Index | 44.3 | 51.1 | — |
Chatbot Arena Elo · Overall | 1455.9 | 1471.0 | — |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.43 | $0.87 | 1.0M tokens (~524 books) | $5.44 | |
| $1.00 | $4.00 | 1.0M tokens (~524 books) | $17.50 | |
| $1.75 | $14.00 | 400K tokens (~200 books) | $48.13 |