💻 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: GPT-6.1 Sol or OpenAI o3-mini?
OpenAI o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $10.00 for output tokens (1.8x cost advantage). In terms of operational performance, GPT-6.1 Sol delivers lower response latency at 520ms TTFT (430ms faster than OpenAI o3-mini) with 135 vs. 98 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 92.4% vs. 79.7% 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
GPT-6.1 Sol
OpenAI o3-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$1.10
OpenAI o3-mini is 1.8x cheaper
Output Cost / 1M Tokens
$10.00
$4.40
OpenAI o3-mini (56.0% lower)
Prompt Cache Read / 1M
$0.100
$0.550
GPT-6.1 Sol is 5.5x cheaper
Prompt Cache Write / 1M
$2.00
$1.10
OpenAI o3-mini is 1.8x cheaper
Context Window (Max Output)
1,075k (128k out)
205k (100k out)
GPT-6.1 Sol (5.3x larger context)
Avg TTFT Response Latency
520ms
950ms
GPT-6.1 Sol (430ms faster)
Generation Speed (Throughput)
135 tok/s
98 tok/s
GPT-6.1 Sol (+37 tok/s faster)
SWE-bench Verified (Coding)
86.4%
49.3%
GPT-6.1 Sol (+37.1% lead)
GPQA Diamond (PhD STEM)
92.4%
79.7%
GPT-6.1 Sol (+12.7% lead)
MMLU-Pro (Multi-Discipline)
91%
83.2%
GPT-6.1 Sol (+7.8% lead)
MATH-500 (Quantitative Logic)
98.8%
97.9%
GPT-6.1 Sol (+0.9% lead)
Inference Value Score (IVR)
62.9 / 100
59.7 / 100
GPT-6.1 Sol (+3.2 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose 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).
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
OpenAI o3-mini is cheaper at $1.10/1M input tokens ($4.40/1M 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: GPT-6.1 Sol or OpenAI o3-mini?
GPT-6.1 Sol delivers faster first-token latency at 520ms TTFT (135 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.
How do GPT-6.1 Sol and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-6.1 Sol scores 86.4% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, GPT-6.1 Sol scores 92.4% versus 79.7% for OpenAI o3-mini (and 98.8% vs 97.9% on MATH-500).
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).
When should you choose OpenAI o3-mini?
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
