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Nnvidia_developer02:04First-partyAnalysis

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Ggoogle_developers_blog08:00First-partyAnalysis

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Aamazon_science23:35First-partyAnalysis

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Ttimothy_b_lee_understanding_ai21:57Analysis

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Llmsys_blog08:00First-partyAnalysis

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Llmsys_blog08:00First-partyAnalysis

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Ttogether_ai_blog08:00First-partyAnalysis

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Llinear_now06:47First-partyAnalysis

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Ttrail_of_bits_blog19:00First-partyAnalysis

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FFireworks AI09:09First-partyAnalysis

AI score61

Fireworks Evaluates DeepSeek V4 Pro Against Fable 5 and Kimi K3

Fireworks tested DeepSeek V4 Pro 0813 on four benchmarks: SWE-Bench Verified, LiveCodeBench v6, Aider Polyglot, and Terminal-Bench 2.1. It scored 95.2% on SWE-Bench Verified, higher than Kimi K3's 92.6% and Fable 5's 85.4%, and 92.0% on LiveCodeBench v6. On cost, DeepSeek V4 Pro spent $0.309 per task solved on SWE-bench, versus $0.808 for Fable 5; on LiveCodeBench the figures were $0.040 and $0.225, respectively. Its weakness is the multilingual breadth of Aider Polyglot, where it scored only 48.9% on Java, versus 74.5% for Fable 5. After oracle routing on a combined set of 409 tasks, accuracy was 92.4%, higher than the 86.6% achieved by Fable 5 alone, at a cost of $0.279 versus $4.510 per task, with 86.3% of tasks routed to V4 Pro.

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Ffireworks_ai09:09First-partyAnalysis

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Ffireworks_ai08:42First-partyAnalysis

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Bbrowser_use_blog08:00First-partyAnalysis

AI score61

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