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DeepSeek

2 posts about DeepSeek. Every summary links to the original.

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DeepSeek V4 Pro 0813 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing
DeepSeek V4 Pro 0813 costs $0.24 per rollout and achieves 62.8% pass@1 on DeepSWE, while GPT-5.6 Sol reaches 72.7% pass@1 at $8.37 per rollout—a 35x price gap. At four attempts, DeepSeek V4 Pro 0813 surpasses Sol, with 88.5% pass@4 versus 85.8%. Sol is faster and more reliable, completing a rollout in 17 minutes and 53 steps, and breaking tests in only 11% of its failures. A cascade strategy—running DeepSeek V4 Pro 0813 first and escalating to Sol on test failure—solves 83.0% of tasks at $3.35 each, outperforming either model alone. Per $100, DeepSeek V4 Pro 0813 solves 260 tasks versus Sol’s 9, making it the value leader for budget-constrained workloads.

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DeepSeek V4 Pro 0813 vs Claude Fable 5 on DeepSWE: Cost, Coding, and Routing
The DeepSWE benchmark comparison between DeepSeek V4 Pro 0813 and Claude Fable 5 reveals a trade-off between cost and accuracy. Claude Fable 5 leads on the first attempt with 69.7% pass@1 versus DeepSeek V4 Pro’s 62.8%, but costs 90 times more per rollout ($21.63 vs $0.24). Under repeated attempts, DeepSeek V4 Pro surpasses Fable, achieving 88.5% pass@4 compared to Fable’s 84.1%. The two models show unusually low per-task correlation (0.39), meaning they fail on different tasks. A cascade strategy that runs DeepSeek V4 Pro first and escalates to Claude Fable 5 only on failures solves 82.7% of tasks at $8.28 per task, outperforming either model used alone.

The best engineering reads, once a week.

Topic

2 posts about DeepSeek. Every summary links to the original.

Paid picks we use ourselves. Links carry a referral code — a subscription through one earns us a commission at no extra cost to you.

Newest first

Together AI
DeepSeek V4 Pro 0813 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing
DeepSeek V4 Pro 0813 costs $0.24 per rollout and achieves 62.8% pass@1 on DeepSWE, while GPT-5.6 Sol reaches 72.7% pass@1 at $8.37 per rollout—a 35x price gap. At four attempts, DeepSeek V4 Pro 0813 surpasses Sol, with 88.5% pass@4 versus 85.8%. Sol is faster and more reliable, completing a rollout in 17 minutes and 53 steps, and breaking tests in only 11% of its failures. A cascade strategy—running DeepSeek V4 Pro 0813 first and escalating to Sol on test failure—solves 83.0% of tasks at $3.35 each, outperforming either model alone. Per $100, DeepSeek V4 Pro 0813 solves 260 tasks versus Sol’s 9, making it the value leader for budget-constrained workloads.

Together AI
DeepSeek V4 Pro 0813 vs Claude Fable 5 on DeepSWE: Cost, Coding, and Routing
The DeepSWE benchmark comparison between DeepSeek V4 Pro 0813 and Claude Fable 5 reveals a trade-off between cost and accuracy. Claude Fable 5 leads on the first attempt with 69.7% pass@1 versus DeepSeek V4 Pro’s 62.8%, but costs 90 times more per rollout ($21.63 vs $0.24). Under repeated attempts, DeepSeek V4 Pro surpasses Fable, achieving 88.5% pass@4 compared to Fable’s 84.1%. The two models show unusually low per-task correlation (0.39), meaning they fail on different tasks. A cascade strategy that runs DeepSeek V4 Pro first and escalates to Claude Fable 5 only on failures solves 82.7% of tasks at $8.28 per task, outperforming either model used alone.

The best engineering reads, once a week.