Which model is better: GLM-5.3-Flash or OpenAI o3-mini?
GLM-5.3-Flash is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.40 vs. $4.40 for output tokens (9.2x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (860ms faster than OpenAI o3-mini) with 175 vs. 98 tok/s throughput. GLM-5.3-Flash leads coding evaluations at 52.8% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 63.5% 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-Flash
OpenAI o3-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$1.10
GLM-5.3-Flash is 9.2x cheaper
Output Cost / 1M Tokens
$0.40
$4.40
GLM-5.3-Flash (90.9% lower)
Prompt Cache Read / 1M
$0.030
$0.550
GLM-5.3-Flash is 18.3x cheaper
Prompt Cache Write / 1M
$0.12
$1.10
GLM-5.3-Flash is 9.2x cheaper
Context Window (Max Output)
262k (16k out)
205k (100k out)
GLM-5.3-Flash (1.3x larger context)
Avg TTFT Response Latency
90ms
950ms
GLM-5.3-Flash (860ms faster)
Generation Speed (Throughput)
175 tok/s
98 tok/s
GLM-5.3-Flash (+77 tok/s faster)
SWE-bench Verified (Coding)
52.8%
49.3%
GLM-5.3-Flash (+3.5% lead)
GPQA Diamond (PhD STEM)
63.5%
79.7%
OpenAI o3-mini (+16.2% lead)
MMLU-Pro (Multi-Discipline)
78.4%
83.2%
OpenAI o3-mini (+4.8% lead)
MATH-500 (Quantitative Logic)
84%
97.9%
OpenAI o3-mini (+13.9% lead)
Inference Value Score (IVR)
76.7 / 100
59.7 / 100
GLM-5.3-Flash (+17 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-Flash (Zhipu AI) for sub-100ms ultra-fast inference model designed for real-time customer support, document classification, and agentic workflows — offering a 262k context window, 90ms TTFT, and $0.12/1M input pricing ($0.030/1M 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).
Which is cheaper: GLM-5.3-Flash or OpenAI o3-mini?
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M 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-Flash or OpenAI o3-mini?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.
How do GLM-5.3-Flash and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 79.7% for OpenAI o3-mini (and 84% vs 97.9% on MATH-500).
When should you choose GLM-5.3-Flash?
Choose GLM-5.3-Flash (Zhipu AI) for sub-100ms ultra-fast inference model designed for real-time customer support, document classification, and agentic workflows — offering a 262k context window, 90ms TTFT, and $0.12/1M input pricing ($0.030/1M 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).
