GLM-5.3 is 68.2% cheaper for input tokens ($0.35 vs. $1.10 per 1M tokens) and $1.00 vs. $4.40 for output tokens (3.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (790ms faster than OpenAI o3-mini) with 120 vs. 98 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 67.0% vs. 79.7% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
Verified Performance & Unit Economics Delta (12 Dimensions)
Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.
Metric / Dimension
GLM-5.3
OpenAI o3-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$0.35
$1.10
GLM-5.3 is 3.1x cheaper
Output Cost / 1M Tokens
$1.00
$4.40
GLM-5.3 (77.3% lower)
Prompt Cache Read / 1M
$0.090
$0.550
GLM-5.3 is 6.1x cheaper
Prompt Cache Write / 1M
$0.35
$1.10
GLM-5.3 is 3.1x cheaper
Context Window (Max Output)
131k (16k out)
205k (100k out)
OpenAI o3-mini (1.6x larger context)
Avg TTFT Response Latency
160ms
950ms
GLM-5.3 (790ms faster)
Generation Speed (Throughput)
120 tok/s
98 tok/s
GLM-5.3 (+22 tok/s faster)
SWE-bench Verified (Coding)
56%
49.3%
GLM-5.3 (+6.7% lead)
GPQA Diamond (PhD STEM)
67%
79.7%
OpenAI o3-mini (+12.7% lead)
MMLU-Pro (Multi-Discipline)
80.5%
83.2%
OpenAI o3-mini (+2.7% lead)
MATH-500 (Quantitative Logic)
88%
97.9%
OpenAI o3-mini (+9.9% lead)
Inference Value Score (IVR)
69.9 / 100
59.7 / 100
GLM-5.3 (+10.2 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose GLM-5.3 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M cached reads).
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
GLM-5.3 is cheaper at $0.35/1M input tokens ($1.00/1M output) compared to $1.10/1M input ($4.40/1M output) for OpenAI o3-mini.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3 or OpenAI o3-mini?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.
How do GLM-5.3 and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3 scores 56% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3 scores 67% versus 79.7% for OpenAI o3-mini (and 88% vs 97.9% on MATH-500).
When should you choose GLM-5.3?
Choose GLM-5.3 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M cached reads).
When should you choose OpenAI o3-mini?
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
