Which model is better: Gemini 3.8 Flash or OpenAI o4-mini?
Gemini 3.8 Flash is 77.3% cheaper for input tokens ($0.25 vs. $1.10 per 1M tokens) and $1.50 vs. $4.40 for output tokens (4.4x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (575ms faster than OpenAI o4-mini) with 210 vs. 125 tok/s throughput. Gemini 3.8 Flash leads coding evaluations at 68.5% SWE-bench Verified vs. 68.1% for OpenAI o4-mini and 79.2% 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 3.8 Flash
OpenAI o4-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$0.25
$1.10
Gemini 3.8 Flash is 4.4x cheaper
Output Cost / 1M Tokens
$1.50
$4.40
Gemini 3.8 Flash (65.9% lower)
Prompt Cache Read / 1M
$0.025
$0.275
Gemini 3.8 Flash is 11.0x cheaper
Prompt Cache Write / 1M
$0.25
$1.10
Gemini 3.8 Flash is 4.4x cheaper
Context Window (Max Output)
1,049k (66k out)
205k (100k out)
Gemini 3.8 Flash (5.1x larger context)
Avg TTFT Response Latency
105ms
680ms
Gemini 3.8 Flash (575ms faster)
Generation Speed (Throughput)
210 tok/s
125 tok/s
Gemini 3.8 Flash (+85 tok/s faster)
SWE-bench Verified (Coding)
68.5%
68.1%
Gemini 3.8 Flash (+0.4% lead)
GPQA Diamond (PhD STEM)
79.2%
81.4%
OpenAI o4-mini (+2.2% lead)
MMLU-Pro (Multi-Discipline)
87.4%
85.6%
Gemini 3.8 Flash (+1.8% lead)
MATH-500 (Quantitative Logic)
95.1%
97.8%
OpenAI o4-mini (+2.7% lead)
Inference Value Score (IVR)
74 / 100
63.7 / 100
Gemini 3.8 Flash (+10.3 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 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M cached reads).
Which is cheaper: Gemini 3.8 Flash or OpenAI o4-mini?
Gemini 3.8 Flash is cheaper at $0.25/1M input tokens ($1.50/1M output) compared to $1.10/1M input ($4.40/1M output) for OpenAI o4-mini.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 3.8 Flash or OpenAI o4-mini?
Gemini 3.8 Flash delivers faster first-token latency at 105ms TTFT (210 tok/s throughput) compared to 680ms TTFT (125 tok/s) for OpenAI o4-mini.
How do Gemini 3.8 Flash and OpenAI o4-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 3.8 Flash scores 68.5% versus 68.1% for OpenAI o4-mini. On GPQA Diamond graduate-level STEM reasoning, Gemini 3.8 Flash scores 79.2% versus 81.4% for OpenAI o4-mini (and 95.1% vs 97.8% on MATH-500).
When should you choose Gemini 3.8 Flash?
Choose Gemini 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M 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).
