DeepSeek-V4.1-Flash-1017 vs GPT-6.1 Sol

A direct, empirical evaluation of DeepSeek-V4.1-Flash-1017 (DeepSeek) against GPT-6.1 Sol (OpenAI).

DeepSeek-V4.1-Flash-1017

Developed by DeepSeek · Open-Weight Distilled Transformer (MIT License) parameters

Top-tier open-weight coding (81.6% SWE-bench Verified), concise reasoning traces with 32% lower token bloat, and fast consumer GPU self-hosting.

GPT-6.1 Sol

Developed by OpenAI · Proprietary Frontier Workhorse Engine parameters

Near-Astra reasoning at 1/5th price ($1.25/$5.00), SWE-bench Verified 74.8%, OSWorld 2.0 desktop agent automation, and sub-80ms Ultrafast Mode.

Metric DeepSeek-V4.1-Flash-1017 GPT-6.1 Sol
SWE-bench Verified 81.6% 74.8%
MMLU-Pro 92.8% 92.4%
MATH-500 94.8% 96.2%
Context Window 128,000 tokens 1,000,000 tokens
Input Pricing (per 1M) $0.14 $1.25
Output Pricing (per 1M) $0.28 $5.00

Architectural & Practical Deployment Analysis

Evaluating DeepSeek-V4.1-Flash-1017 (DeepSeek) alongside GPT-6.1 Sol (OpenAI) highlights key technical trade-offs across neural parameter scale and compute efficiency. DeepSeek-V4.1-Flash-1017 executes across Open-Weight Distilled Transformer (MIT License) total parameters with Multi-Head Latent Attention (MLA) Core active per token, whereas GPT-6.1 Sol operates on Proprietary Frontier Workhorse Engine parameters with Dynamic Speculative MoE Core on NVIDIA GB200 active per token.

On SWE-bench Verified software engineering tasks, DeepSeek-V4.1-Flash-1017 achieves 81.6% autonomous resolution rate, compared to 74.8% for GPT-6.1 Sol. On complex reasoning benchmarks, DeepSeek-V4.1-Flash-1017 posts 92.8% on MMLU-Pro and 94.8% on MATH-500, against 92.4% and 96.2% respectively for GPT-6.1 Sol.

From an operational economics perspective, processing 10,000,000 mixed tokens (7M input / 3M output) costs approximately $1.82 on DeepSeek-V4.1-Flash-1017 versus $23.75 on GPT-6.1 Sol.

Recommendation: Deploy DeepSeek-V4.1-Flash-1017 when your infrastructure prioritizes top-tier open-weight coding (81.6% swe-bench verified), concise reasoning traces with 32% lower token bloat, and fast consumer gpu self-hosting.. Deploy GPT-6.1 Sol when workload requirements favor near-astra reasoning at 1/5th price ($1.25/$5.00), swe-bench verified 74.8%, osworld 2.0 desktop agent automation, and sub-80ms ultrafast mode..