💻 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 Grok 3?
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 (100ms faster than Grok 3) with 135 vs. 88 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 65.8% for Grok 3 and 92.4% vs. 84.6% 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
GPT-6.1 Sol
Grok 3
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$3.00
GPT-6.1 Sol is 1.5x cheaper
Output Cost / 1M Tokens
$10.00
$15.00
GPT-6.1 Sol (33.3% lower)
Prompt Cache Read / 1M
$0.100
$0.750
GPT-6.1 Sol is 7.5x cheaper
Prompt Cache Write / 1M
$2.00
$3.00
GPT-6.1 Sol is 1.5x cheaper
Context Window (Max Output)
1,075k (128k out)
134k (16k out)
GPT-6.1 Sol (8.0x larger context)
Avg TTFT Response Latency
520ms
620ms
GPT-6.1 Sol (100ms faster)
Generation Speed (Throughput)
135 tok/s
88 tok/s
GPT-6.1 Sol (+47 tok/s faster)
SWE-bench Verified (Coding)
86.4%
65.8%
GPT-6.1 Sol (+20.6% lead)
GPQA Diamond (PhD STEM)
92.4%
84.6%
GPT-6.1 Sol (+7.8% lead)
MMLU-Pro (Multi-Discipline)
91%
80%
GPT-6.1 Sol (+11.0% lead)
MATH-500 (Quantitative Logic)
98.8%
89.8%
GPT-6.1 Sol (+9.0% lead)
Inference Value Score (IVR)
62.9 / 100
52.7 / 100
GPT-6.1 Sol (+10.2 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 Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M cached reads).
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 Grok 3.
Which model has lower TTFT latency and higher tok/s throughput: GPT-6.1 Sol or Grok 3?
GPT-6.1 Sol delivers faster first-token latency at 520ms TTFT (135 tok/s throughput) compared to 620ms TTFT (88 tok/s) for Grok 3.
How do GPT-6.1 Sol and Grok 3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-6.1 Sol scores 86.4% versus 65.8% for Grok 3. On GPQA Diamond graduate-level STEM reasoning, GPT-6.1 Sol scores 92.4% versus 84.6% for Grok 3 (and 98.8% vs 89.8% 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 Grok 3?
Choose Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M cached reads).
