GLM-5.3-Flash is 95.2% cheaper for input tokens ($0.12 vs. $2.50 per 1M tokens) and $0.40 vs. $10.00 for output tokens (20.8x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (190ms faster than GPT-4o) with 175 vs. 100 tok/s throughput. GLM-5.3-Flash leads coding evaluations at 52.8% SWE-bench Verified vs. 48.0% for GPT-4o and 63.5% vs. 53.6% 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
GPT-4o
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$2.50
GLM-5.3-Flash is 20.8x cheaper
Output Cost / 1M Tokens
$0.40
$10.00
GLM-5.3-Flash (96.0% lower)
Prompt Cache Read / 1M
$0.030
$1.250
GLM-5.3-Flash is 41.7x cheaper
Prompt Cache Write / 1M
$0.12
$2.50
GLM-5.3-Flash is 20.8x cheaper
Context Window (Max Output)
262k (16k out)
131k (16k out)
GLM-5.3-Flash (2.0x larger context)
Avg TTFT Response Latency
90ms
280ms
GLM-5.3-Flash (190ms faster)
Generation Speed (Throughput)
175 tok/s
100 tok/s
GLM-5.3-Flash (+75 tok/s faster)
SWE-bench Verified (Coding)
52.8%
48%
GLM-5.3-Flash (+4.8% lead)
GPQA Diamond (PhD STEM)
63.5%
53.6%
GLM-5.3-Flash (+9.9% lead)
MMLU-Pro (Multi-Discipline)
78.4%
75.9%
GLM-5.3-Flash (+2.5% lead)
MATH-500 (Quantitative Logic)
84%
76.6%
GLM-5.3-Flash (+7.4% lead)
Inference Value Score (IVR)
76.7 / 100
47.6 / 100
GLM-5.3-Flash (+29.1 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).
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M output) compared to $2.50/1M input ($10.00/1M output) for GPT-4o.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3-Flash or GPT-4o?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 280ms TTFT (100 tok/s) for GPT-4o.
How do GLM-5.3-Flash and GPT-4o compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 48% for GPT-4o. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 53.6% for GPT-4o (and 84% vs 76.6% 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 GPT-4o?
Choose GPT-4o (OpenAI) for general enterprise assistants, multimodal customer support, and structured JSON output pipelines — offering a 131k context window, 280ms TTFT, and $2.50/1M input pricing ($1.250/1M cached reads).
