DeepSeek V3 is 99.1% cheaper for input tokens ($0.14 vs. $15.00 per 1M tokens) and $0.28 vs. $60.00 for output tokens (107.1x cost advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (2190ms faster than o1) with 78 vs. 48 tok/s throughput. o1 leads coding evaluations at 48.9% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 78.0% 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
o1
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$15.00
DeepSeek V3 is 107.1x cheaper
Output Cost / 1M Tokens
$0.28
$60.00
DeepSeek V3 (99.5% lower)
Prompt Cache Read / 1M
$0.014
$7.500
DeepSeek V3 is 535.7x cheaper
Prompt Cache Write / 1M
$0.14
$15.00
DeepSeek V3 is 107.1x cheaper
Context Window (Max Output)
131k (8k out)
205k (100k out)
o1 (1.6x larger context)
Avg TTFT Response Latency
410ms
2600ms
DeepSeek V3 (2190ms faster)
Generation Speed (Throughput)
78 tok/s
48 tok/s
DeepSeek V3 (+30 tok/s faster)
SWE-bench Verified (Coding)
42%
48.9%
o1 (+6.9% lead)
GPQA Diamond (PhD STEM)
59.1%
78%
o1 (+18.9% lead)
MMLU-Pro (Multi-Discipline)
75.9%
83.3%
o1 (+7.4% lead)
MATH-500 (Quantitative Logic)
90.2%
96.4%
o1 (+6.2% lead)
Inference Value Score (IVR)
75 / 100
37.2 / 100
DeepSeek V3 (+37.8 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 $15.00/1M input ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or o1?
DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do DeepSeek V3 and o1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 78% for o1 (and 90.2% vs 96.4% 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 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).
