Which model is better: Gemini 3.1 Pro or OpenAI o4-mini?
OpenAI o4-mini is 12.0% cheaper for input tokens ($1.10 vs. $1.25 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.1x cost advantage). In terms of operational performance, Gemini 3.1 Pro delivers lower response latency at 420ms TTFT (260ms faster than OpenAI o4-mini) with 98 vs. 125 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 68.1% for OpenAI o4-mini and 82.4% vs. 81.4% 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
Gemini 3.1 Pro
OpenAI o4-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$1.25
$1.10
OpenAI o4-mini is 1.1x cheaper
Output Cost / 1M Tokens
$10.00
$4.40
OpenAI o4-mini (56.0% lower)
Prompt Cache Read / 1M
$0.310
$0.275
OpenAI o4-mini is 1.1x cheaper
Prompt Cache Write / 1M
$1.25
$1.10
OpenAI o4-mini is 1.1x cheaper
Context Window (Max Output)
1,049k (66k out)
205k (100k out)
Gemini 3.1 Pro (5.1x larger context)
Avg TTFT Response Latency
420ms
680ms
Gemini 3.1 Pro (260ms faster)
Generation Speed (Throughput)
98 tok/s
125 tok/s
OpenAI o4-mini (+27 tok/s faster)
SWE-bench Verified (Coding)
71.8%
68.1%
Gemini 3.1 Pro (+3.7% lead)
GPQA Diamond (PhD STEM)
82.4%
81.4%
Gemini 3.1 Pro (+1.0% lead)
MMLU-Pro (Multi-Discipline)
89.5%
85.6%
Gemini 3.1 Pro (+3.9% lead)
MATH-500 (Quantitative Logic)
96.8%
97.8%
OpenAI o4-mini (+1.0% lead)
Inference Value Score (IVR)
60 / 100
63.7 / 100
OpenAI o4-mini (+3.7 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).
Which is cheaper: Gemini 3.1 Pro or OpenAI o4-mini?
OpenAI o4-mini is cheaper at $1.10/1M input tokens ($4.40/1M output) compared to $1.25/1M input ($10.00/1M output) for Gemini 3.1 Pro.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 3.1 Pro or OpenAI o4-mini?
Gemini 3.1 Pro delivers faster first-token latency at 420ms TTFT (98 tok/s throughput) compared to 680ms TTFT (125 tok/s) for OpenAI o4-mini.
How do Gemini 3.1 Pro and OpenAI o4-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 3.1 Pro scores 71.8% versus 68.1% for OpenAI o4-mini. On GPQA Diamond graduate-level STEM reasoning, Gemini 3.1 Pro scores 82.4% versus 81.4% for OpenAI o4-mini (and 96.8% vs 97.8% on MATH-500).
When should you choose Gemini 3.1 Pro?
Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).
When should you choose OpenAI o4-mini?
Choose OpenAI o4-mini (OpenAI) for automated PR review, high-volume agentic coding loops, SQL/data analysis, and visual document reasoning — offering a 204k context window, 680ms TTFT, and $1.10/1M input pricing ($0.275/1M cached reads).
