💻 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: Claude 3.7 Sonnet or GPT-6.1 Sol?
GPT-6.1 Sol is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $10.00 vs. $15.00 for output tokens (1.5x cost advantage). In terms of operational performance, GPT-6.1 Sol delivers lower response latency at 520ms TTFT (20ms faster than Claude 3.7 Sonnet) with 135 vs. 72 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 70.3% for Claude 3.7 Sonnet and 92.4% vs. 78.5% 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
Claude 3.7 Sonnet
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$3.00
$2.00
GPT-6.1 Sol is 1.5x cheaper
Output Cost / 1M Tokens
$15.00
$10.00
GPT-6.1 Sol (33.3% lower)
Prompt Cache Read / 1M
$0.300
$0.100
GPT-6.1 Sol is 3.0x cheaper
Prompt Cache Write / 1M
$3.75
$2.00
GPT-6.1 Sol is 1.9x cheaper
Context Window (Max Output)
205k (64k out)
1,075k (128k out)
GPT-6.1 Sol (5.3x larger context)
Avg TTFT Response Latency
540ms
520ms
GPT-6.1 Sol (20ms faster)
Generation Speed (Throughput)
72 tok/s
135 tok/s
GPT-6.1 Sol (+63 tok/s faster)
SWE-bench Verified (Coding)
70.3%
86.4%
GPT-6.1 Sol (+16.1% lead)
GPQA Diamond (PhD STEM)
78.5%
92.4%
GPT-6.1 Sol (+13.9% lead)
MMLU-Pro (Multi-Discipline)
88%
91%
GPT-6.1 Sol (+3.0% lead)
MATH-500 (Quantitative Logic)
96.2%
98.8%
GPT-6.1 Sol (+2.6% lead)
Inference Value Score (IVR)
54.3 / 100
62.9 / 100
GPT-6.1 Sol (+8.6 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: Claude 3.7 Sonnet or GPT-6.1 Sol?
GPT-6.1 Sol is cheaper at $2.00/1M input tokens ($10.00/1M output) compared to $3.00/1M input ($15.00/1M output) for Claude 3.7 Sonnet.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.7 Sonnet or GPT-6.1 Sol?
GPT-6.1 Sol delivers faster first-token latency at 520ms TTFT (135 tok/s throughput) compared to 540ms TTFT (72 tok/s) for Claude 3.7 Sonnet.
How do Claude 3.7 Sonnet and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.7 Sonnet scores 70.3% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, Claude 3.7 Sonnet scores 78.5% versus 92.4% for GPT-6.1 Sol (and 96.2% vs 98.8% on MATH-500).
When should you choose Claude 3.7 Sonnet?
Choose Claude 3.7 Sonnet (Anthropic) for full-stack repository development, complex code refactoring, and agentic tool use with predictable prompt cache economics — offering a 204k context window, 540ms TTFT, and $3.00/1M input pricing ($0.300/1M 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).
