DeepSeek V4 Pro: Tops SWE-Bench & Cuts Cost per Task by 3x vs. Fable 5

This post introduces DeepSeek V4 Pro 0813 to the Fireworks AI platform, detailing its performance on SWE-Bench Verified, LiveCodeBench v6, Aider Polyglot v1, and Terminal-Bench 2.1. It highlights DeepSeek V4 Pro's superior accuracy on SWE-Bench and LiveCodeBench compared to Kimi K3 and Fable 5, and its significant cost advantage over Fable 5. The post also discusses oracle routing strategies between DeepSeek V4 Pro and Fable 5, demonstrating a substantial improvement in accuracy and cost reduction. It notes DeepSeek V4 Pro's limitations in multi-language breadth, particularly in Java, and emphasizes the benefit of using specialized models with dynamic routing. Training support for DeepSeek V4 Pro is now available, including SFT, DPO, and RFT, with a focus on co-optimized training and serving infrastructure. The post also provides insights into DeepSeek's native harness (dsh) and its implications for tool calling consistency.