OpenAI o3-mini is 92.7% cheaper for input tokens ($1.10 vs. $15.00 per 1M tokens) and $4.40 vs. $60.00 for output tokens (13.6x cost advantage). In terms of operational performance, OpenAI o3-mini delivers lower response latency at 950ms TTFT (1650ms faster than o1) with 98 vs. 48 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 48.9% for o1 and 79.7% vs. 78.0% 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
o1
OpenAI o3-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$15.00
$1.10
OpenAI o3-mini is 13.6x cheaper
Output Cost / 1M Tokens
$60.00
$4.40
OpenAI o3-mini (92.7% lower)
Prompt Cache Read / 1M
$7.500
$0.550
OpenAI o3-mini is 13.6x cheaper
Prompt Cache Write / 1M
$15.00
$1.10
OpenAI o3-mini is 13.6x cheaper
Context Window (Max Output)
205k (100k out)
205k (100k out)
Equal Context Window
Avg TTFT Response Latency
2600ms
950ms
OpenAI o3-mini (1650ms faster)
Generation Speed (Throughput)
48 tok/s
98 tok/s
OpenAI o3-mini (+50 tok/s faster)
SWE-bench Verified (Coding)
48.9%
49.3%
OpenAI o3-mini (+0.4% lead)
GPQA Diamond (PhD STEM)
78%
79.7%
OpenAI o3-mini (+1.7% lead)
MMLU-Pro (Multi-Discipline)
83.3%
83.2%
o1 (+0.1% lead)
MATH-500 (Quantitative Logic)
96.4%
97.9%
OpenAI o3-mini (+1.5% lead)
Inference Value Score (IVR)
37.2 / 100
59.7 / 100
OpenAI o3-mini (+22.5 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
OpenAI o3-mini is cheaper at $1.10/1M input tokens ($4.40/1M output) compared to $15.00/1M input ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: o1 or OpenAI o3-mini?
OpenAI o3-mini delivers faster first-token latency at 950ms TTFT (98 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do o1 and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, o1 scores 48.9% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, o1 scores 78% versus 79.7% for OpenAI o3-mini (and 96.4% vs 97.9% on MATH-500).
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).
When should you choose OpenAI o3-mini?
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
