DeepSeek V3 is 60.0% cheaper for input tokens ($0.14 vs. $0.35 per 1M tokens) and $0.28 vs. $1.00 for output tokens (2.5x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (250ms faster than DeepSeek V3) with 120 vs. 78 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 67.0% vs. 59.1% 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
DeepSeek V3
GLM-5.3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$0.35
DeepSeek V3 is 2.5x cheaper
Output Cost / 1M Tokens
$0.28
$1.00
DeepSeek V3 (72.0% lower)
Prompt Cache Read / 1M
$0.014
$0.090
DeepSeek V3 is 6.4x cheaper
Prompt Cache Write / 1M
$0.14
$0.35
DeepSeek V3 is 2.5x cheaper
Context Window (Max Output)
131k (8k out)
131k (16k out)
Equal Context Window
Avg TTFT Response Latency
410ms
160ms
GLM-5.3 (250ms faster)
Generation Speed (Throughput)
78 tok/s
120 tok/s
GLM-5.3 (+42 tok/s faster)
SWE-bench Verified (Coding)
42%
56%
GLM-5.3 (+14.0% lead)
GPQA Diamond (PhD STEM)
59.1%
67%
GLM-5.3 (+7.9% lead)
MMLU-Pro (Multi-Discipline)
75.9%
80.5%
GLM-5.3 (+4.6% lead)
MATH-500 (Quantitative Logic)
90.2%
88%
DeepSeek V3 (+2.2% lead)
Inference Value Score (IVR)
75 / 100
69.9 / 100
DeepSeek V3 (+5.1 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).
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M output) compared to $0.35/1M input ($1.00/1M output) for GLM-5.3.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or GLM-5.3?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do DeepSeek V3 and GLM-5.3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 56% for GLM-5.3. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 67% for GLM-5.3 (and 90.2% vs 88% on MATH-500).
When should you choose DeepSeek V3?
Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M cached reads).
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).
