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Fine-Tuning DeepSeek v3 & R1 to optimize quality, latency, & cost

Fireworks

Customization of DeepSeek R1 & V3, through Quantization Aware Fine Tuning, is now available as part of Fireworks https://fireworks.ai/blog/fireoptimizer.

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Blogs Fireworks

BlogsDeepSeek V4 Pro: Tops SWE-Bench & Cuts Cost per Task by 3x vs. Fable 5Fireworks BlogsReinforcement Fine Tuning: Train expert open models to surpass closed frontier modelsFireworks BlogsDeep-Dive into LLM Fine-TuningFireworks BlogsFireAttention V4: Industry-Leading Latency and Cost Efficiency with FP4Fireworks BlogsPartnering with Meta: Bringing Llama 3.2 to Fireworks for Fine-Tuning and InferenceFireworks BlogsDistillation with Reasoning: Can DeepSeek R1 Teach Better Than Humans?Fireworks BlogsThere Is Only One Key Difference Between Observability 1.0 and 2.0Honeycomb Products & ServicesGitBook stands with UkraineGitbook Products & ServicesA new quality layer for documentation: WhatGitbook NewsUse Monitoring Insights to Optimize CostThenewstack NewsHow This Open Source Bionic Leg Could Revolutionize ProstheticsThenewstack LearnStop guessing whether your AI analytics stack works.Motherduck BlogsAI in abundanceMistral BlogsSpaces: A CLI Built for Humans and AgentsMistral BlogsUnlocking the potential of vision language models on satellite imagery through fine-tuningMistral BlogsVoxtral transcribes at the speed of sound.Mistral BlogsLearn How to Optimize Usage with New Docker Hub DashboardsDocker BlogsAI Video Generators, Social Media Trends 2026Heygen BlogsHeyGen + Agent.ai: Bringing AI video to the No. 1 professional agent networkHeygen Blogs30 Best AI Sales Automation Tools 2026 (Tested)Heygen