Which model is better: GLM-5.3-Flash or Grok 3 Mini?
GLM-5.3-Flash is 60.0% cheaper for input tokens ($0.12 vs. $0.30 per 1M tokens) and $0.40 vs. $1.20 for output tokens (2.5x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (60ms faster than Grok 3 Mini) with 175 vs. 160 tok/s throughput. Grok 3 Mini leads coding evaluations at 54.0% SWE-bench Verified vs. 52.8% for GLM-5.3-Flash and 68.0% 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 Mini
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$0.30
GLM-5.3-Flash is 2.5x cheaper
Output Cost / 1M Tokens
$0.40
$1.20
GLM-5.3-Flash (66.7% lower)
Prompt Cache Read / 1M
$0.030
$0.080
GLM-5.3-Flash is 2.7x cheaper
Prompt Cache Write / 1M
$0.12
$0.30
GLM-5.3-Flash is 2.5x cheaper
Context Window (Max Output)
262k (16k out)
131k (16k out)
GLM-5.3-Flash (2.0x larger context)
Avg TTFT Response Latency
90ms
150ms
GLM-5.3-Flash (60ms faster)
Generation Speed (Throughput)
175 tok/s
160 tok/s
GLM-5.3-Flash (+15 tok/s faster)
SWE-bench Verified (Coding)
52.8%
54%
Grok 3 Mini (+1.2% lead)
GPQA Diamond (PhD STEM)
63.5%
68%
Grok 3 Mini (+4.5% lead)
MMLU-Pro (Multi-Discipline)
78.4%
80%
Grok 3 Mini (+1.6% lead)
MATH-500 (Quantitative Logic)
84%
87%
Grok 3 Mini (+3.0% lead)
Inference Value Score (IVR)
76.7 / 100
69.2 / 100
GLM-5.3-Flash (+7.5 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 Mini (xAI) for high-speed reasoning model providing rapid answers and code generation with chain-of-thought capabilities at edge pricing — offering a 131k context window, 150ms TTFT, and $0.30/1M input pricing ($0.080/1M cached reads).
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M output) compared to $0.30/1M input ($1.20/1M output) for Grok 3 Mini.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3-Flash or Grok 3 Mini?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 150ms TTFT (160 tok/s) for Grok 3 Mini.
How do GLM-5.3-Flash and Grok 3 Mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 54% for Grok 3 Mini. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 68% for Grok 3 Mini (and 84% vs 87% 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 Mini?
Choose Grok 3 Mini (xAI) for high-speed reasoning model providing rapid answers and code generation with chain-of-thought capabilities at edge pricing — offering a 131k context window, 150ms TTFT, and $0.30/1M input pricing ($0.080/1M cached reads).
