Which model is better: Gemini 4 Argon or GPT-4o Mini?
GPT-4o Mini is 92.5% cheaper for input tokens ($0.15 vs. $2.00 per 1M tokens) and $0.60 vs. $10.00 for output tokens (13.3x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (630ms faster than Gemini 4 Argon) with 140 vs. 115 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 93.8% vs. 40.2% 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 4 Argon
GPT-4o Mini
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$0.15
GPT-4o Mini is 13.3x cheaper
Output Cost / 1M Tokens
$10.00
$0.60
GPT-4o Mini (94.0% lower)
Prompt Cache Read / 1M
$0.100
$0.075
GPT-4o Mini is 1.3x cheaper
Prompt Cache Write / 1M
$0.50
$0.15
GPT-4o Mini is 3.3x cheaper
Context Window (Max Output)
1,024k (1000k out)
131k (16k out)
Gemini 4 Argon (7.8x larger context)
Avg TTFT Response Latency
850ms
220ms
GPT-4o Mini (630ms faster)
Generation Speed (Throughput)
115 tok/s
140 tok/s
GPT-4o Mini (+25 tok/s faster)
SWE-bench Verified (Coding)
84.5%
41%
Gemini 4 Argon (+43.5% lead)
GPQA Diamond (PhD STEM)
93.8%
40.2%
Gemini 4 Argon (+53.6% lead)
MMLU-Pro (Multi-Discipline)
91.4%
68%
Gemini 4 Argon (+23.4% lead)
MATH-500 (Quantitative Logic)
98.2%
70.2%
Gemini 4 Argon (+28.0% lead)
Inference Value Score (IVR)
62.6 / 100
67.2 / 100
GPT-4o Mini (+4.6 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 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
GPT-4o Mini is cheaper at $0.15/1M input tokens ($0.60/1M output) compared to $2.00/1M input ($10.00/1M output) for Gemini 4 Argon.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 4 Argon or GPT-4o Mini?
GPT-4o Mini delivers faster first-token latency at 220ms TTFT (140 tok/s throughput) compared to 850ms TTFT (115 tok/s) for Gemini 4 Argon.
How do Gemini 4 Argon and GPT-4o Mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 4 Argon scores 84.5% versus 41% for GPT-4o Mini. On GPQA Diamond graduate-level STEM reasoning, Gemini 4 Argon scores 93.8% versus 40.2% for GPT-4o Mini (and 98.2% vs 70.2% on MATH-500).
When should you choose Gemini 4 Argon?
Choose Gemini 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
When should you choose GPT-4o Mini?
Choose GPT-4o Mini (OpenAI) for high-volume classification, lightweight RAG chatbots, and structured JSON extraction — offering a 131k context window, 220ms TTFT, and $0.15/1M input pricing ($0.075/1M cached reads).
