Which model is better: Gemini 4 Argon or OpenAI o3?
Gemini 4 Argon and OpenAI o3 share identical input pricing at $2.00 per 1M tokens ($10.00 vs. $8.00 output). In terms of operational performance, Gemini 4 Argon delivers lower response latency at 850ms TTFT (300ms faster than OpenAI o3) with 115 vs. 82 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 71.7% for OpenAI o3 and 93.8% vs. 87.7% 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
OpenAI o3
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$2.00
Identical Pricing
Output Cost / 1M Tokens
$10.00
$8.00
OpenAI o3 (20.0% lower)
Prompt Cache Read / 1M
$0.100
$0.500
Gemini 4 Argon is 5.0x cheaper
Prompt Cache Write / 1M
$0.50
$2.00
Gemini 4 Argon is 4.0x cheaper
Context Window (Max Output)
1,024k (1000k out)
205k (100k out)
Gemini 4 Argon (5.0x larger context)
Avg TTFT Response Latency
850ms
1150ms
Gemini 4 Argon (300ms faster)
Generation Speed (Throughput)
115 tok/s
82 tok/s
Gemini 4 Argon (+33 tok/s faster)
SWE-bench Verified (Coding)
84.5%
71.7%
Gemini 4 Argon (+12.8% lead)
GPQA Diamond (PhD STEM)
93.8%
87.7%
Gemini 4 Argon (+6.1% lead)
MMLU-Pro (Multi-Discipline)
91.4%
89.8%
Gemini 4 Argon (+1.6% lead)
MATH-500 (Quantitative Logic)
98.2%
98.6%
OpenAI o3 (+0.4% lead)
Inference Value Score (IVR)
62.6 / 100
60.6 / 100
Gemini 4 Argon (+2 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).
Both Gemini 4 Argon and OpenAI o3 share identical input pricing at $2.00/1M tokens.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 4 Argon or OpenAI o3?
Gemini 4 Argon delivers faster first-token latency at 850ms TTFT (115 tok/s throughput) compared to 1150ms TTFT (82 tok/s) for OpenAI o3.
How do Gemini 4 Argon and OpenAI o3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 4 Argon scores 84.5% versus 71.7% for OpenAI o3. On GPQA Diamond graduate-level STEM reasoning, Gemini 4 Argon scores 93.8% versus 87.7% for OpenAI o3 (and 98.2% vs 98.6% 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 OpenAI o3?
Choose OpenAI o3 (OpenAI) for algorithmic synthesis, mathematical verification, PhD-level scientific research, and multi-step tool planning — offering a 204k context window, 1150ms TTFT, and $2.00/1M input pricing ($0.500/1M cached reads).
