GLM-5.3 is 97.7% cheaper for input tokens ($0.35 vs. $15.00 per 1M tokens) and $1.00 vs. $60.00 for output tokens (42.9x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (2440ms faster than o1) with 120 vs. 48 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 48.9% for o1 and 67.0% 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
o1
Net Delta / Advantage
Input Cost / 1M Tokens
$0.35
$15.00
GLM-5.3 is 42.9x cheaper
Output Cost / 1M Tokens
$1.00
$60.00
GLM-5.3 (98.3% lower)
Prompt Cache Read / 1M
$0.090
$7.500
GLM-5.3 is 83.3x cheaper
Prompt Cache Write / 1M
$0.35
$15.00
GLM-5.3 is 42.9x cheaper
Context Window (Max Output)
131k (16k out)
205k (100k out)
o1 (1.6x larger context)
Avg TTFT Response Latency
160ms
2600ms
GLM-5.3 (2440ms faster)
Generation Speed (Throughput)
120 tok/s
48 tok/s
GLM-5.3 (+72 tok/s faster)
SWE-bench Verified (Coding)
56%
48.9%
GLM-5.3 (+7.1% lead)
GPQA Diamond (PhD STEM)
67%
78%
o1 (+11.0% lead)
MMLU-Pro (Multi-Discipline)
80.5%
83.3%
o1 (+2.8% lead)
MATH-500 (Quantitative Logic)
88%
96.4%
o1 (+8.4% lead)
Inference Value Score (IVR)
69.9 / 100
37.2 / 100
GLM-5.3 (+32.7 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 $15.00/1M input ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: GLM-5.3 or o1?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do GLM-5.3 and o1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GLM-5.3 scores 56% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, GLM-5.3 scores 67% versus 78% for o1 (and 88% vs 96.4% 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 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).
