GLM-5.3-Flash is 95.2% cheaper for input tokens ($0.12 vs. $2.50 per 1M tokens) and $0.40 vs. $12.50 for output tokens (20.8x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (390ms faster than Grok 4) with 175 vs. 95 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 52.8% for GLM-5.3-Flash and 86.2% vs. 63.5% 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
Grok 4
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
$12.50
GLM-5.3-Flash (96.8% lower)
Prompt Cache Read / 1M
$0.030
$0.500
GLM-5.3-Flash is 16.7x cheaper
Prompt Cache Write / 1M
$0.12
$2.50
GLM-5.3-Flash is 20.8x cheaper
Context Window (Max Output)
262k (16k out)
262k (66k out)
Equal Context Window
Avg TTFT Response Latency
90ms
480ms
GLM-5.3-Flash (390ms faster)
Generation Speed (Throughput)
175 tok/s
95 tok/s
GLM-5.3-Flash (+80 tok/s faster)
SWE-bench Verified (Coding)
52.8%
73.2%
Grok 4 (+20.4% lead)
GPQA Diamond (PhD STEM)
63.5%
86.2%
Grok 4 (+22.7% lead)
MMLU-Pro (Multi-Discipline)
78.4%
89.9%
Grok 4 (+11.5% lead)
MATH-500 (Quantitative Logic)
84%
97.6%
Grok 4 (+13.6% lead)
Inference Value Score (IVR)
76.7 / 100
57.6 / 100
GLM-5.3-Flash (+19.1 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 ($12.50/1M output) for Grok 4.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3-Flash or Grok 4?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 480ms TTFT (95 tok/s) for Grok 4.
How do GLM-5.3-Flash and Grok 4 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 73.2% for Grok 4. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 86.2% for Grok 4 (and 84% vs 97.6% 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 Grok 4?
Choose Grok 4 (xAI) for real-time financial/market intelligence, PhD-level STEM problem solving, and autonomous code generation — offering a 262k context window, 480ms TTFT, and $2.50/1M input pricing ($0.500/1M cached reads).
