Compare · ModelsLive · 2 picked · head to head
DeepSeek V3.2 vs GLM 5.3
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
GLM 5.3 wins on 9/9 benchmarks
GLM 5.3 wins 9 of 9 shared benchmarks. Leads in speed · agentic · knowledge.
Category leads
speed·GLM 5.3agentic·GLM 5.3knowledge·GLM 5.3general·GLM 5.3math·GLM 5.3
Hype vs Reality
Attention vs performance
DeepSeek V3.2
#146 by perf·no signal
GLM 5.3
#73 by perf·#3 by attention
Best value
DeepSeek V3.2
2.0x better value than GLM 5.3
DeepSeek V3.2
150.9 pts/$
$0.32/M
GLM 5.3
77.1 pts/$
$0.73/M
Vendor risk
Mixed exposure
One or more vendors flagged
DeepSeek
$3.4B·Tier 1
z-ai
private · undisclosed
Head to head
9 benchmarks · 2 models
DeepSeek V3.2GLM 5.3
Artificial Analysis · Quality Index
GLM 5.3 leads by +3.1
DeepSeek V3.2
41.7
GLM 5.3
44.8
APEX-Agents
GLM 5.3 leads by +35.3
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
DeepSeek V3.2
21.3
GLM 5.3
56.6
Chess Puzzles
GLM 5.3 leads by +24.2
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
DeepSeek V3.2
9.5
GLM 5.3
33.7
Dtbench
GLM 5.3 leads by +3.5
DeepSeek V3.2
76.0
GLM 5.3
79.5
GPQA diamond
GLM 5.3 leads by +10.4
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
DeepSeek V3.2
81.1
GLM 5.3
91.5
Lmca
GLM 5.3 leads by +31.4
DeepSeek V3.2
33.9
GLM 5.3
65.3
OTIS Mock AIME 2024-2025
GLM 5.3 leads by +3.3
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
DeepSeek V3.2
87.8
GLM 5.3
91.1
Proofbench
GLM 5.3 leads by +41.0
DeepSeek V3.2
8.0
GLM 5.3
49.0
SimpleQA Verified
GLM 5.3 leads by +13.5
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
DeepSeek V3.2
27.5
GLM 5.3
41.0
Full benchmark table
| Benchmark | DeepSeek V3.2 | GLM 5.3 |
|---|---|---|
Artificial Analysis · Quality Index | 41.7 | 44.8 |
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 21.3 | 56.6 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 9.5 | 33.7 |
Dtbench | 76.0 | 79.5 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 81.1 | 91.5 |
Lmca | 33.9 | 65.3 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 87.8 | 91.1 |
Proofbench | 8.0 | 49.0 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 27.5 | 41.0 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $0.26 | $0.38 | 164K tokens (~82 books) | $2.90 | |
| $0.07 | $1.40 | 1.0M tokens (~524 books) | $4.02 |