GLM-5.3-Flash is 96.0% cheaper for input tokens ($0.12 vs. $3.00 per 1M tokens) and $0.40 vs. $15.00 for output tokens (25.0x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (530ms faster than Grok 3) with 175 vs. 88 tok/s throughput. Grok 3 leads coding evaluations at 65.8% SWE-bench Verified vs. 52.8% for GLM-5.3-Flash and 84.6% 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 3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$3.00
GLM-5.3-Flash is 25.0x cheaper
Output Cost / 1M Tokens
$0.40
$15.00
GLM-5.3-Flash (97.3% lower)
Prompt Cache Read / 1M
$0.030
$0.750
GLM-5.3-Flash is 25.0x cheaper
Prompt Cache Write / 1M
$0.12
$3.00
GLM-5.3-Flash is 25.0x cheaper
Context Window (Max Output)
262k (16k out)
134k (16k out)
GLM-5.3-Flash (2.0x larger context)
Avg TTFT Response Latency
90ms
620ms
GLM-5.3-Flash (530ms faster)
Generation Speed (Throughput)
175 tok/s
88 tok/s
GLM-5.3-Flash (+87 tok/s faster)
SWE-bench Verified (Coding)
52.8%
65.8%
Grok 3 (+13.0% lead)
GPQA Diamond (PhD STEM)
63.5%
84.6%
Grok 3 (+21.1% lead)
MMLU-Pro (Multi-Discipline)
78.4%
80%
Grok 3 (+1.6% lead)
MATH-500 (Quantitative Logic)
84%
89.8%
Grok 3 (+5.8% lead)
Inference Value Score (IVR)
76.7 / 100
52.7 / 100
GLM-5.3-Flash (+24 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 Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M cached reads).
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M output) compared to $3.00/1M input ($15.00/1M output) for Grok 3.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3-Flash or Grok 3?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 620ms TTFT (88 tok/s) for Grok 3.
How do GLM-5.3-Flash and Grok 3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 65.8% for Grok 3. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 84.6% for Grok 3 (and 84% vs 89.8% 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 3?
Choose Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M cached reads).
