Which model is better: Claude Opus 5.5 or GLM-5.3-Flash?
GLM-5.3-Flash is 97.0% cheaper for input tokens ($0.12 vs. $4.00 per 1M tokens) and $0.40 vs. $20.00 for output tokens (33.3x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (590ms faster than Claude Opus 5.5) with 175 vs. 95 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 52.8% for GLM-5.3-Flash and 93.2% 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
Claude Opus 5.5
GLM-5.3-Flash
Net Delta / Advantage
Input Cost / 1M Tokens
$4.00
$0.12
GLM-5.3-Flash is 33.3x cheaper
Output Cost / 1M Tokens
$20.00
$0.40
GLM-5.3-Flash (98.0% lower)
Prompt Cache Read / 1M
$0.200
$0.030
GLM-5.3-Flash is 6.7x cheaper
Prompt Cache Write / 1M
$5.00
$0.12
GLM-5.3-Flash is 41.7x cheaper
Context Window (Max Output)
1,024k (128k out)
262k (16k out)
Claude Opus 5.5 (3.9x larger context)
Avg TTFT Response Latency
680ms
90ms
GLM-5.3-Flash (590ms faster)
Generation Speed (Throughput)
95 tok/s
175 tok/s
GLM-5.3-Flash (+80 tok/s faster)
SWE-bench Verified (Coding)
89.9%
52.8%
Claude Opus 5.5 (+37.1% lead)
GPQA Diamond (PhD STEM)
93.2%
63.5%
Claude Opus 5.5 (+29.7% lead)
MMLU-Pro (Multi-Discipline)
92.1%
78.4%
Claude Opus 5.5 (+13.7% lead)
MATH-500 (Quantitative Logic)
98%
84%
Claude Opus 5.5 (+14.0% lead)
Inference Value Score (IVR)
57.8 / 100
76.7 / 100
GLM-5.3-Flash (+18.9 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
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).
Which is cheaper: Claude Opus 5.5 or GLM-5.3-Flash?
GLM-5.3-Flash is cheaper at $0.12/1M input tokens ($0.40/1M output) compared to $4.00/1M input ($20.00/1M output) for Claude Opus 5.5.
Which model has lower TTFT latency and higher tok/s throughput: Claude Opus 5.5 or GLM-5.3-Flash?
GLM-5.3-Flash delivers faster first-token latency at 90ms TTFT (175 tok/s throughput) compared to 680ms TTFT (95 tok/s) for Claude Opus 5.5.
How do Claude Opus 5.5 and GLM-5.3-Flash compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude Opus 5.5 scores 89.9% versus 52.8% for GLM-5.3-Flash. On GPQA Diamond graduate-level STEM reasoning, Claude Opus 5.5 scores 93.2% versus 63.5% for GLM-5.3-Flash (and 98% vs 84% on MATH-500).
When should you choose Claude Opus 5.5?
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
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).
