DeepSeek R1 cuts input token costs by 96.3% compared to o1 ($0.55 vs. $15.00 per 1M input tokens; $2.19 vs. $60.00/1M output). For autonomous software engineering, DeepSeek R1 leads on SWE-bench Verified (49.2% vs. 48.9%), while o1 edges ahead on GPQA Diamond scientific reasoning (78.0%). In real-time API production, DeepSeek R1 achieves a faster 1450ms TTFT latency (58.0 tokens/sec).
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 R1
o1
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$15.00
DeepSeek R1 is 27.3x cheaper
Output Cost / 1M Tokens
$2.19
$60.00
DeepSeek R1 (96.4% lower)
Prompt Cache Read / 1M
$0.140
$7.500
DeepSeek R1 is 53.6x cheaper
Prompt Cache Write / 1M
$0.55
$15.00
DeepSeek R1 is 27.3x cheaper
Context Window (Max Output)
131k (33k out)
205k (100k out)
o1 (1.6x larger context)
Avg TTFT Response Latency
1450ms
2600ms
DeepSeek R1 (1150ms faster)
Generation Speed (Throughput)
58 tok/s
48 tok/s
DeepSeek R1 (+10 tok/s faster)
SWE-bench Verified (Coding)
49.2%
48.9%
DeepSeek R1 (+0.3% lead)
GPQA Diamond (PhD STEM)
71.5%
78%
o1 (+6.5% lead)
MMLU-Pro (Multi-Discipline)
84%
83.3%
DeepSeek R1 (+0.7% lead)
MATH-500 (Quantitative Logic)
97.3%
96.4%
DeepSeek R1 (+0.9% lead)
Inference Value Score (IVR)
64.8 / 100
37.2 / 100
DeepSeek R1 (+27.6 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
DeepSeek R1 is cheaper at $0.55/1M input tokens ($2.19/1M 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 R1 or o1?
DeepSeek R1 delivers faster first-token latency at 1450ms TTFT (58 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do DeepSeek R1 and o1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 78% for o1 (and 97.3% vs 96.4% on MATH-500).
When should you choose DeepSeek R1?
Deploy DeepSeek R1 when your architecture requires 49.2% SWE-bench coding accuracy, 71.5% GPQA Diamond reasoning, and 131k context at $0.55/1M input ($0.140/1M cached read).
When should you choose o1?
Select o1 for workloads prioritizing 2600ms TTFT latency, 48.0 tokens/sec throughput, and $15.00/1M input pricing ($7.500/1M cached read).
