Post-training by Nebius Token Factory
Deeply customized models built for your business.
Our Post-training service turns open-source LLMs into high-performance, production-grade systems, fine-tuned on your data, optimized with distillation and speculative decoding and deployed instantly on Nebius multi-node infrastructure.
You get better accuracy, lower latency and dramatically lower costs, without managing distributed systems.
What you get
Deep customization
Generic LLMs rarely match your domain, workflows, or style. The Post-training service fine-tunes 30+ open-source models using LoRA or full FT, and adds structure-aware decoding so outputs follow your schema: JSON, SQL, code, or internal formats.
Long-context training and reasoning-aligned templates ensure models behave consistently in real production settings.
Speed to production
Training large models is slow and brittle on single-node setups. Nebius provides a distributed, multi-node backend that scales from 8 to 512 GPUs with no code changes, delivering higher throughput, stable long-context training (up to 131k tokens) and faster iteration cycles.
You reach production quality sooner, with fewer failed runs and shorter development loops.
Lower total cost
Large models are expensive to serve at scale. Our built-in distillation and speculative decoding pipelines compress powerful teachers into compact students that run 3–5× faster and cost significantly less to operate.
Combined with transparent per-token pricing and zero idle GPU charges, production costs stay predictable and often substantially lower than competing platforms.
Build production-ready models
Fine-tune frontier models
Customize DeepSeek V3, GPT-OSS 120B, Qwen3 Coder 480B and more using LoRA or full supervised FT.
Models keep your schema, tone and constraints, from strict JSON formats to domain-specific terminology, while benefiting from stable multi-node training and long-context support.
Distill for efficiency
Compress massive teachers into compact student models that are 3–5× faster at inference. Reduce latency and cost while keeping reasoning quality high. Ideal for real-time agents and large-scale production workloads.
Deploy with confidence
Move from training to serving in one step. Deploy to Nebius endpoints, serverless APIs, GPU-on-demand, or dedicated enterprise clusters with SLAs and zero-retention. Scale from prototype to production without infrastructure overhead.
Explore our guides
Discover our documentation, step-by-step guides and practical cookbook to level up your experience.
How it works: the Post-Training Factory pipeline
Train
Choose a base model and run fine-tuning across Nebius GPU clusters. Scale jobs across nodes with Nebius Papyrax, our JAX-based distributed training framework.
Distill
Use teacher-student distillation to compress reasoning into smaller, faster models tailored to your tasks.
Spec decode
Add training for structured, reliable outputs, making models production-safe for enterprise systems.
Deploy
With one click, your model is live on Nebius: serverless endpoints, on-demand GPU, or dedicated enterprise clusters with SLAs and zero-retention inference.
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Fine-tune models with confidence
Fine-tune models with confidence
Our intuitive platform makes it easy to configure training and monitor progress.
Start your journey with these in-depth guides
Beyond prompting: fine-tuning LLMs
Learn how to customize open-source models for your specific requirements and improve performance on domain-specific tasks.
Make AI work for you
Discover how Nebius Token Factory' fine-tuning service transforms generic models into specialized solutions with 30+ leading open-source models.
Transparent, competitive pricing
Pay only for the compute resources you use during LoRA fine-tuning and inference. No monthly fees, infrastructure costs, or hidden charges.
Questions and answers
- Conversational AI: domain-specific assistants for HR, finance, or support; multilingual chatbots with product knowledge, agents that reliably follow company rules.
- Specialized content & code: generators tuned to your brand voice, documentation tools aligned with your standards, code assistants trained on your repos.
- Knowledge systems: accurate Q&A and research assistants in healthcare, legal, or SaaS, powered by your internal datasets.
- Cost-optimized models: distilled variants that deliver advanced reasoning at 3–5× faster inference and lower $/request, ideal for real-time or high-volume use.