Gemini 4 Argon delivers superior capability and a 20.0% input cost advantage over GPT-5. At $2.00 vs. $2.50 per 1M input tokens ($10.00 output), Gemini leads SWE-bench Verified (84.5% vs. 74.9%) and GPQA Diamond (93.8% vs. 85.4%). Conversely, GPT-5 posts a 340ms TTFT, responding 510ms faster despite lower throughput (105 vs. 115 tok/s).
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-5
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$2.50
Gemini 4 Argon is 1.3x cheaper
Output Cost / 1M Tokens
$10.00
$10.00
Identical Output Pricing
Prompt Cache Read / 1M
$0.100
$0.625
Gemini 4 Argon is 6.3x cheaper
Prompt Cache Write / 1M
$0.50
$2.50
Gemini 4 Argon is 5.0x cheaper
Context Window (Max Output)
1,024k (1000k out)
410k (128k out)
Gemini 4 Argon (2.5x larger context)
Avg TTFT Response Latency
850ms
340ms
GPT-5 (510ms faster)
Generation Speed (Throughput)
115 tok/s
105 tok/s
Gemini 4 Argon (+10 tok/s faster)
SWE-bench Verified (Coding)
84.5%
74.9%
Gemini 4 Argon (+9.6% lead)
GPQA Diamond (PhD STEM)
93.8%
85.4%
Gemini 4 Argon (+8.4% lead)
MMLU-Pro (Multi-Discipline)
91.4%
90.8%
Gemini 4 Argon (+0.6% lead)
MATH-500 (Quantitative Logic)
98.2%
98%
Gemini 4 Argon (+0.2% lead)
Inference Value Score (IVR)
62.6 / 100
59.2 / 100
Gemini 4 Argon (+3.4 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).
Gemini 4 Argon is cheaper at $2.00/1M input tokens ($10.00/1M output) compared to $2.50/1M input ($10.00/1M output) for GPT-5.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 4 Argon or GPT-5?
GPT-5 delivers faster first-token latency at 340ms TTFT (105 tok/s throughput) compared to 850ms TTFT (115 tok/s) for Gemini 4 Argon.
How do Gemini 4 Argon and GPT-5 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 4 Argon scores 84.5% versus 74.9% for GPT-5. On GPQA Diamond graduate-level STEM reasoning, Gemini 4 Argon scores 93.8% versus 85.4% for GPT-5 (and 98.2% vs 98% 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-5?
Choose GPT-5 (OpenAI) for complex enterprise automation, full-stack software engineering, multimodal agent orchestration, and scientific synthesis — offering a 409k context window, 340ms TTFT, and $2.50/1M input pricing ($0.625/1M cached reads).
