GLM-5.3 is 86.0% cheaper for input tokens ($0.35 vs. $2.50 per 1M tokens) and $1.00 vs. $10.00 for output tokens (7.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (120ms faster than GPT-4o) with 120 vs. 100 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 48.0% for GPT-4o and 67.0% 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
GPT-4o
Net Delta / Advantage
Input Cost / 1M Tokens
$0.35
$2.50
GLM-5.3 is 7.1x cheaper
Output Cost / 1M Tokens
$1.00
$10.00
GLM-5.3 (90.0% lower)
Prompt Cache Read / 1M
$0.090
$1.250
GLM-5.3 is 13.9x cheaper
Prompt Cache Write / 1M
$0.35
$2.50
GLM-5.3 is 7.1x cheaper
Context Window (Max Output)
131k (16k out)
131k (16k out)
Equal Context Window
Avg TTFT Response Latency
160ms
280ms
GLM-5.3 (120ms faster)
Generation Speed (Throughput)
120 tok/s
100 tok/s
GLM-5.3 (+20 tok/s faster)
SWE-bench Verified (Coding)
56%
48%
GLM-5.3 (+8.0% lead)
GPQA Diamond (PhD STEM)
67%
53.6%
GLM-5.3 (+13.4% lead)
MMLU-Pro (Multi-Discipline)
80.5%
75.9%
GLM-5.3 (+4.6% lead)
MATH-500 (Quantitative Logic)
88%
76.6%
GLM-5.3 (+11.4% lead)
Inference Value Score (IVR)
69.9 / 100
47.6 / 100
GLM-5.3 (+22.3 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 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M cached reads).
GLM-5.3 is cheaper at $0.35/1M input tokens ($1.00/1M 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 or GPT-4o?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 280ms TTFT (100 tok/s) for GPT-4o.
How do GLM-5.3 and GPT-4o compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3 scores 56% versus 48% for GPT-4o. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3 scores 67% versus 53.6% for GPT-4o (and 88% vs 76.6% on MATH-500).
When should you choose GLM-5.3?
Choose GLM-5.3 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M 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).
