GLM-5.3-Flash is 99.2% cheaper for input tokens ($0.12 vs. $15.00 per 1M tokens) and $0.40 vs. $60.00 for output tokens (125.0x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (2510ms faster than o1) with 175 vs. 48 tok/s throughput. GLM-5.3-Flash leads coding evaluations at 52.8% SWE-bench Verified vs. 48.9% for o1 and 63.5% vs. 78.0% 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
o1
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$15.00
GLM-5.3-Flash is 125.0x cheaper
Output Cost / 1M Tokens
$0.40
$60.00
GLM-5.3-Flash (99.3% lower)
Prompt Cache Read / 1M
$0.030
$7.500
GLM-5.3-Flash is 250.0x cheaper
Prompt Cache Write / 1M
$0.12
$15.00
GLM-5.3-Flash is 125.0x cheaper
Context Window (Max Output)
262k (16k out)
205k (100k out)
GLM-5.3-Flash (1.3x larger context)
Avg TTFT Response Latency
90ms
2600ms
GLM-5.3-Flash (2510ms faster)
Generation Speed (Throughput)
175 tok/s
48 tok/s
GLM-5.3-Flash (+127 tok/s faster)
SWE-bench Verified (Coding)
52.8%
48.9%
GLM-5.3-Flash (+3.9% lead)
GPQA Diamond (PhD STEM)
63.5%
78%
o1 (+14.5% lead)
MMLU-Pro (Multi-Discipline)
78.4%
83.3%
o1 (+4.9% lead)
MATH-500 (Quantitative Logic)
84%
96.4%
o1 (+12.4% lead)
Inference Value Score (IVR)
76.7 / 100
37.2 / 100
GLM-5.3-Flash (+39.5 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).
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M output) compared to $15.00/1M input ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3-Flash or o1?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do GLM-5.3-Flash and o1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3-Flash scores 52.8% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3-Flash scores 63.5% versus 78% for o1 (and 84% vs 96.4% 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 o1?
Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).
