DeepSeek V3 is 94.4% cheaper for input tokens ($0.14 vs. $2.50 per 1M tokens) and $0.28 vs. $10.00 for output tokens (17.9x cost advantage). In terms of operational performance, GPT-5 delivers lower response latency at 340ms TTFT (70ms faster than DeepSeek V3) with 105 vs. 78 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 85.4% 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
GPT-5
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$2.50
DeepSeek V3 is 17.9x cheaper
Output Cost / 1M Tokens
$0.28
$10.00
DeepSeek V3 (97.2% lower)
Prompt Cache Read / 1M
$0.014
$0.625
DeepSeek V3 is 44.6x cheaper
Prompt Cache Write / 1M
$0.14
$2.50
DeepSeek V3 is 17.9x cheaper
Context Window (Max Output)
131k (8k out)
410k (128k out)
GPT-5 (3.1x larger context)
Avg TTFT Response Latency
410ms
340ms
GPT-5 (70ms faster)
Generation Speed (Throughput)
78 tok/s
105 tok/s
GPT-5 (+27 tok/s faster)
SWE-bench Verified (Coding)
42%
74.9%
GPT-5 (+32.9% lead)
GPQA Diamond (PhD STEM)
59.1%
85.4%
GPT-5 (+26.3% lead)
MMLU-Pro (Multi-Discipline)
75.9%
90.8%
GPT-5 (+14.9% lead)
MATH-500 (Quantitative Logic)
90.2%
98%
GPT-5 (+7.8% lead)
Inference Value Score (IVR)
75 / 100
59.2 / 100
DeepSeek V3 (+15.8 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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: DeepSeek V3 or GPT-5?
GPT-5 delivers faster first-token latency at 340ms TTFT (105 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do DeepSeek V3 and GPT-5 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 74.9% for GPT-5. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 85.4% for GPT-5 (and 90.2% vs 98% 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 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).
