💻 Coding (SWE) WinnerGPT-6.1 Sol 86.4% SWE-bench · 96.8% HumanEval
🧠 STEM Reasoning WinnerGPT-6.1 Sol 92.4% GPQA · 98.8% MATH-500
Which model is better: Gemini 2.0 Flash or GPT-6.1 Sol?
Gemini 2.0 Flash is 95.0% cheaper for input tokens ($0.10 vs. $2.00 per 1M tokens) and $0.40 vs. $10.00 for output tokens (20.0x cost advantage). In terms of operational performance, Gemini 2.0 Flash delivers lower response latency at 280ms TTFT (240ms faster than GPT-6.1 Sol) with 185 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 51.8% for Gemini 2.0 Flash and 92.4% vs. 63.6% 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 2.0 Flash
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$0.10
$2.00
Gemini 2.0 Flash is 20.0x cheaper
Output Cost / 1M Tokens
$0.40
$10.00
Gemini 2.0 Flash (96.0% lower)
Prompt Cache Read / 1M
$0.025
$0.100
Gemini 2.0 Flash is 4.0x cheaper
Prompt Cache Write / 1M
$0.10
$2.00
Gemini 2.0 Flash is 20.0x cheaper
Context Window (Max Output)
1,073k (8k out)
1,075k (128k out)
GPT-6.1 Sol (1.0x larger context)
Avg TTFT Response Latency
280ms
520ms
Gemini 2.0 Flash (240ms faster)
Generation Speed (Throughput)
185 tok/s
135 tok/s
Gemini 2.0 Flash (+50 tok/s faster)
SWE-bench Verified (Coding)
51.8%
86.4%
GPT-6.1 Sol (+34.6% lead)
GPQA Diamond (PhD STEM)
63.6%
92.4%
GPT-6.1 Sol (+28.8% lead)
MMLU-Pro (Multi-Discipline)
78.2%
91%
GPT-6.1 Sol (+12.8% lead)
MATH-500 (Quantitative Logic)
91.1%
98.8%
GPT-6.1 Sol (+7.7% lead)
Inference Value Score (IVR)
77.7 / 100
62.9 / 100
Gemini 2.0 Flash (+14.8 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
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).
Which is cheaper: Gemini 2.0 Flash or GPT-6.1 Sol?
Gemini 2.0 Flash is cheaper at $0.10/1M input tokens ($0.40/1M output) compared to $2.00/1M input ($10.00/1M output) for GPT-6.1 Sol.
Which model has lower TTFT latency and higher tok/s throughput: Gemini 2.0 Flash or GPT-6.1 Sol?
Gemini 2.0 Flash delivers faster first-token latency at 280ms TTFT (185 tok/s throughput) compared to 520ms TTFT (135 tok/s) for GPT-6.1 Sol.
How do Gemini 2.0 Flash and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 2.0 Flash scores 51.8% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, Gemini 2.0 Flash scores 63.6% versus 92.4% for GPT-6.1 Sol (and 91.1% vs 98.8% on MATH-500).
When should you choose Gemini 2.0 Flash?
Choose Gemini 2.0 Flash (Google DeepMind) for legacy high-throughput multimodal pipelines migrating to Gemini 3.8 Flash — offering a 1,073k context window, 280ms TTFT, and $0.10/1M input pricing ($0.025/1M 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).
