DeepSeek V4 Pro 0813 vs Claude Fable 5 on DeepSWE: Cost, Coding, and Routing

This post introduces a detailed comparison between DeepSeek V4 Pro 0813 and Claude Fable 5 on the DeepSWE benchmark, focusing on cost, coding performance, and routing strategies. It quantifies the performance differences (pass@1, pass@k), cost per rollout, and cost-effectiveness (solves per $100). It also analyzes failure modes, domain-specific strengths, and language-specific performance. A key contribution is the demonstration of a cascaded routing strategy (DeepSeek V4 Pro 0813 first, then Claude Fable 5 if needed) that achieves 82.7% task completion at $8.28 per task, significantly outperforming Claude Fable 5 alone at $21.63 per task. The analysis reveals a low per-task correlation (0.39) between the two models, indicating complementary strengths that make routing effective.
More from the Long Context Task Decomposition trail
- DeepSeek V4 Pro 0813 vs GPT-5.6 Sol on DeepSWE: Cost, Coding, and Routing
- Serving MiniMax-M3 for efficient inference: Unlocking 1M-Token Context and Multimodality Without Regrets
- Serving DeepSeek-V4: why million-token context is an inference systems problem
- DeepSeek-V4 Pro now available on Together AI
- Plan, divide, and conquer: How weak models excel at long context tasks