💻 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 Flash Vision (Exp) or GPT-6.1 Sol?
DeepSeek V4 Flash Vision (Exp) is 89.0% cheaper for input tokens ($0.22 vs. $2.00 per 1M tokens) and $0.65 vs. $10.00 for output tokens (9.1x cost advantage). In terms of operational performance, DeepSeek V4 Flash Vision (Exp) delivers lower response latency at 310ms TTFT (210ms faster than GPT-6.1 Sol) with 165 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 77.4% for DeepSeek V4 Flash Vision (Exp) and 92.4% vs. 91.3% 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 Flash Vision (Exp)
GPT-6.1 Sol
Net Delta / Advantage
Input Cost / 1M Tokens
$0.22
$2.00
DeepSeek V4 Flash Vision (Exp) is 9.1x cheaper
Output Cost / 1M Tokens
$0.65
$10.00
DeepSeek V4 Flash Vision (Exp) (93.5% lower)
Prompt Cache Read / 1M
$0.007
$0.100
DeepSeek V4 Flash Vision (Exp) is 14.5x cheaper
Prompt Cache Write / 1M
$0.22
$2.00
DeepSeek V4 Flash Vision (Exp) is 9.1x cheaper
Context Window (Max Output)
1,049k (128k out)
1,075k (128k out)
GPT-6.1 Sol (1.0x larger context)
Avg TTFT Response Latency
310ms
520ms
DeepSeek V4 Flash Vision (Exp) (210ms faster)
Generation Speed (Throughput)
165 tok/s
135 tok/s
DeepSeek V4 Flash Vision (Exp) (+30 tok/s faster)
SWE-bench Verified (Coding)
77.4%
86.4%
GPT-6.1 Sol (+9.0% lead)
GPQA Diamond (PhD STEM)
91.3%
92.4%
GPT-6.1 Sol (+1.1% lead)
MMLU-Pro (Multi-Discipline)
87.3%
91%
GPT-6.1 Sol (+3.7% lead)
MATH-500 (Quantitative Logic)
96.4%
98.8%
GPT-6.1 Sol (+2.4% lead)
Inference Value Score (IVR)
81.6 / 100
62.9 / 100
DeepSeek V4 Flash Vision (Exp) (+18.7 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
25.0M Tokens
500K50M250M500M+
5.0M Tokens
100K25M75M150M+
50% Cached
0% (Uncached)25%50% (Typical Agent)95% Max
Estimated Monthly Spend
DeepSeek V4 Flash Vision (Exp)$6.09
$0.22/1M in · $0.65/1M out
Prompt Cache: $0.007/1M read · $0.22/1M write
GPT-6.1 Sol$76.25
$2.00/1M in · $10.00/1M out
Prompt Cache: $0.100/1M read · $2.00/1M write
Projected Monthly Cost Reduction
$70.16 / mo
(92.0% lower cost with DeepSeek V4 Flash Vision (Exp))
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: DeepSeek V4 Flash Vision (Exp) or GPT-6.1 Sol?
DeepSeek V4 Flash Vision (Exp) is cheaper at $0.22/1M input tokens ($0.65/1M 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 Flash Vision (Exp) or GPT-6.1 Sol?
DeepSeek V4 Flash Vision (Exp) delivers faster first-token latency at 310ms TTFT (165 tok/s throughput) compared to 520ms TTFT (135 tok/s) for GPT-6.1 Sol.
How do DeepSeek V4 Flash Vision (Exp) and GPT-6.1 Sol compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V4 Flash Vision (Exp) scores 77.4% versus 86.4% for GPT-6.1 Sol. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Flash Vision (Exp) scores 91.3% versus 92.4% for GPT-6.1 Sol (and 96.4% vs 98.8% on MATH-500).
When should you choose DeepSeek V4 Flash Vision (Exp)?
Choose DeepSeek V4 Flash Vision (Exp) (DeepSeek) for ultra-low-cost open-weight multimodal MoE built for high-throughput visual document OCR, chart interpretation, and real-time autonomous coding agents — offering a 1,048k context window, 310ms TTFT, and $0.22/1M input pricing ($0.007/1M 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).
