💻 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: DeepSeek R1 or GPT-6.1 Sol?
DeepSeek R1 is 72.5% cheaper for input tokens ($0.55 vs. $2.00 per 1M tokens) and $2.19 vs. $10.00 for output tokens (3.6x cost advantage). In terms of operational performance, GPT-6.1 Sol delivers lower response latency at 520ms TTFT (930ms faster than DeepSeek R1) with 135 vs. 58 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 92.4% vs. 71.5% 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
DeepSeek R1
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$2.00
DeepSeek R1 is 3.6x cheaper
Output Cost / 1M Tokens
$2.19
$10.00
DeepSeek R1 (78.1% lower)
Prompt Cache Read / 1M
$0.140
$0.100
GPT-6.1 Sol is 1.4x cheaper
Prompt Cache Write / 1M
$0.55
$2.00
DeepSeek R1 is 3.6x cheaper
Context Window (Max Output)
131k (33k out)
1,075k (128k out)
GPT-6.1 Sol (8.2x larger context)
Avg TTFT Response Latency
1450ms
520ms
GPT-6.1 Sol (930ms faster)
Generation Speed (Throughput)
58 tok/s
135 tok/s
GPT-6.1 Sol (+77 tok/s faster)
SWE-bench Verified (Coding)
49.2%
86.4%
GPT-6.1 Sol (+37.2% lead)
GPQA Diamond (PhD STEM)
71.5%
92.4%
GPT-6.1 Sol (+20.9% lead)
MMLU-Pro (Multi-Discipline)
84%
91%
GPT-6.1 Sol (+7.0% lead)
MATH-500 (Quantitative Logic)
97.3%
98.8%
GPT-6.1 Sol (+1.5% lead)
Inference Value Score (IVR)
64.8 / 100
62.9 / 100
DeepSeek R1 (+1.9 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).
DeepSeek R1 is cheaper at $0.55/1M input tokens ($2.19/1M 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: DeepSeek R1 or GPT-6.1 Sol?
GPT-6.1 Sol delivers faster first-token latency at 520ms TTFT (135 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do DeepSeek R1 and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 92.4% for GPT-6.1 Sol (and 97.3% vs 98.8% on MATH-500).
When should you choose DeepSeek R1?
Choose DeepSeek R1 (DeepSeek) for open-weight chain-of-thought reasoning, synthetic data distillation, and complex mathematical verification — offering a 131k context window, 1450ms TTFT, and $0.55/1M input pricing ($0.140/1M 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).
