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 (180ms faster than GPT-5) with 120 vs. 105 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 56.0% for GLM-5.3 and 85.4% vs. 67.0% 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
GPT-5
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
$0.625
GLM-5.3 is 6.9x cheaper
Prompt Cache Write / 1M
$0.35
$2.50
GLM-5.3 is 7.1x cheaper
Context Window (Max Output)
131k (16k out)
410k (128k out)
GPT-5 (3.1x larger context)
Avg TTFT Response Latency
160ms
340ms
GLM-5.3 (180ms faster)
Generation Speed (Throughput)
120 tok/s
105 tok/s
GLM-5.3 (+15 tok/s faster)
SWE-bench Verified (Coding)
56%
74.9%
GPT-5 (+18.9% lead)
GPQA Diamond (PhD STEM)
67%
85.4%
GPT-5 (+18.4% lead)
MMLU-Pro (Multi-Discipline)
80.5%
90.8%
GPT-5 (+10.3% lead)
MATH-500 (Quantitative Logic)
88%
98%
GPT-5 (+10.0% lead)
Inference Value Score (IVR)
69.9 / 100
59.2 / 100
GLM-5.3 (+10.7 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-5.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3 or GPT-5?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 340ms TTFT (105 tok/s) for GPT-5.
How do GLM-5.3 and GPT-5 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3 scores 56% versus 74.9% for GPT-5. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3 scores 67% versus 85.4% for GPT-5 (and 88% vs 98% 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-5?
Choose GPT-5 (OpenAI) for complex enterprise automation, full-stack software engineering, multimodal agent orchestration, and scientific synthesis — offering a 409k context window, 340ms TTFT, and $2.50/1M input pricing ($0.625/1M cached reads).
