Which model is better: Gemini 4 Argon or GPT-6.1 Sol?
Gemini 4 Argon and GPT-6.1 Sol share identical input pricing at $2.00 per 1M tokens ($10.00 vs. $10.00 output). In terms of operational performance, GPT-6.1 Sol delivers lower response latency at 520ms TTFT (330ms faster than Gemini 4 Argon) with 135 vs. 115 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 84.5% for Gemini 4 Argon and 92.4% vs. 93.8% 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-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$2.00
Identical Pricing
Output Cost / 1M Tokens
$10.00
$10.00
Identical Output Pricing
Prompt Cache Read / 1M
$0.100
$0.100
Identical Cache Read Pricing
Prompt Cache Write / 1M
$0.50
$2.00
Gemini 4 Argon is 4.0x cheaper
Context Window (Max Output)
1,024k (1000k out)
1,075k (128k out)
GPT-6.1 Sol (1.1x larger context)
Avg TTFT Response Latency
850ms
520ms
GPT-6.1 Sol (330ms faster)
Generation Speed (Throughput)
115 tok/s
135 tok/s
GPT-6.1 Sol (+20 tok/s faster)
SWE-bench Verified (Coding)
84.5%
86.4%
GPT-6.1 Sol (+1.9% lead)
GPQA Diamond (PhD STEM)
93.8%
92.4%
Gemini 4 Argon (+1.4% lead)
MMLU-Pro (Multi-Discipline)
91.4%
91%
Gemini 4 Argon (+0.4% lead)
MATH-500 (Quantitative Logic)
98.2%
98.8%
GPT-6.1 Sol (+0.6% lead)
Inference Value Score (IVR)
62.6 / 100
62.9 / 100
GPT-6.1 Sol (+0.3 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 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).
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
Both Gemini 4 Argon and GPT-6.1 Sol share identical input pricing at $2.00/1M tokens.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 4 Argon or GPT-6.1 Sol?
GPT-6.1 Sol delivers faster first-token latency at 520ms TTFT (135 tok/s throughput) compared to 850ms TTFT (115 tok/s) for Gemini 4 Argon.
How do Gemini 4 Argon and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 4 Argon scores 84.5% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, Gemini 4 Argon scores 93.8% versus 92.4% for GPT-6.1 Sol (and 98.2% vs 98.8% 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-6.1 Sol?
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).
