💻 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 V3 or GPT-6.1 Sol?
DeepSeek V3 is 93.0% cheaper for input tokens ($0.14 vs. $2.00 per 1M tokens) and $0.28 vs. $10.00 for output tokens (14.3x cost advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (110ms faster than GPT-6.1 Sol) with 78 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 92.4% vs. 59.1% 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 V3
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$2.00
DeepSeek V3 is 14.3x cheaper
Output Cost / 1M Tokens
$0.28
$10.00
DeepSeek V3 (97.2% lower)
Prompt Cache Read / 1M
$0.014
$0.100
DeepSeek V3 is 7.1x cheaper
Prompt Cache Write / 1M
$0.14
$2.00
DeepSeek V3 is 14.3x cheaper
Context Window (Max Output)
131k (8k out)
1,075k (128k out)
GPT-6.1 Sol (8.2x larger context)
Avg TTFT Response Latency
410ms
520ms
DeepSeek V3 (110ms faster)
Generation Speed (Throughput)
78 tok/s
135 tok/s
GPT-6.1 Sol (+57 tok/s faster)
SWE-bench Verified (Coding)
42%
86.4%
GPT-6.1 Sol (+44.4% lead)
GPQA Diamond (PhD STEM)
59.1%
92.4%
GPT-6.1 Sol (+33.3% lead)
MMLU-Pro (Multi-Discipline)
75.9%
91%
GPT-6.1 Sol (+15.1% lead)
MATH-500 (Quantitative Logic)
90.2%
98.8%
GPT-6.1 Sol (+8.6% lead)
Inference Value Score (IVR)
75 / 100
62.9 / 100
DeepSeek V3 (+12.1 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 V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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 V3 or GPT-6.1 Sol?
DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 520ms TTFT (135 tok/s) for GPT-6.1 Sol.
How do DeepSeek V3 and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 92.4% for GPT-6.1 Sol (and 90.2% vs 98.8% on MATH-500).
When should you choose DeepSeek V3?
Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M 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).
