💻 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 V4 Pro or GPT-6.1 Sol?
DeepSeek V4 Pro is 34.0% cheaper for input tokens ($1.32 vs. $2.00 per 1M tokens) and $3.96 vs. $10.00 for output tokens (1.5x cost advantage). In terms of operational performance, Both models demonstrate comparable response latency around 520ms TTFT (78 vs. 135 tok/s). GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 80.6% for DeepSeek V4 Pro and 92.4% vs. 90.1% 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 V4 Pro
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$1.32
$2.00
DeepSeek V4 Pro is 1.5x cheaper
Output Cost / 1M Tokens
$3.96
$10.00
DeepSeek V4 Pro (60.4% lower)
Prompt Cache Read / 1M
$0.145
$0.100
GPT-6.1 Sol is 1.4x cheaper
Prompt Cache Write / 1M
$1.32
$2.00
DeepSeek V4 Pro is 1.5x cheaper
Context Window (Max Output)
1,024k (128k out)
1,075k (128k out)
GPT-6.1 Sol (1.1x larger context)
Avg TTFT Response Latency
520ms
520ms
Identical Latency
Generation Speed (Throughput)
78 tok/s
135 tok/s
GPT-6.1 Sol (+57 tok/s faster)
SWE-bench Verified (Coding)
80.6%
86.4%
GPT-6.1 Sol (+5.8% lead)
GPQA Diamond (PhD STEM)
90.1%
92.4%
GPT-6.1 Sol (+2.3% lead)
MMLU-Pro (Multi-Discipline)
88.4%
91%
GPT-6.1 Sol (+2.6% lead)
MATH-500 (Quantitative Logic)
97.3%
98.8%
GPT-6.1 Sol (+1.5% lead)
Inference Value Score (IVR)
67 / 100
62.9 / 100
DeepSeek V4 Pro (+4.1 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 V4 Pro is cheaper at $1.32/1M input tokens ($3.96/1M 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 V4 Pro or GPT-6.1 Sol?
Both DeepSeek V4 Pro and GPT-6.1 Sol deliver comparable response times around 520ms TTFT.
How do DeepSeek V4 Pro and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V4 Pro scores 80.6% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Pro scores 90.1% versus 92.4% for GPT-6.1 Sol (and 97.3% vs 98.8% on MATH-500).
When should you choose DeepSeek V4 Pro?
Choose DeepSeek V4 Pro (DeepSeek) for open-weight 1.6T MoE powerhouse designed for cost-effective full-repository code generation, mathematical reasoning, and persistent chain-of-thought multi-step agent workflows — offering a 1,024k context window, 520ms TTFT, and $1.32/1M input pricing ($0.145/1M 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).
