Fine-tuning developer tools
Every listing tagged fine-tuning, A to Z: 7 tools across 1 category. Listed in alphabetical order, not ranked.
Amazon Bedrock Model Customization
Amazon Bedrock's model customization: supervised fine-tuning, reinforcement fine-tuning with reward functions in AWS Lambda, and distillation from a large teacher model into a smaller one. Billed per training token times epochs, from $1 per million on Nova Micro, plus $1.95 per model a month for storage. Parameter-efficient custom models run on demand at the base model's price.
Axolotl
Free, open-source (Apache-2.0) fine-tuning framework: one YAML config covers dataset prep, training, evaluation and quantization. Full fine-tuning, LoRA, QLoRA, DPO, KTO, ORPO and GRPO on NVIDIA or AMD GPUs, multi-GPU with FSDP2 or DeepSpeed and multi-node with Torchrun or Ray.
Fireworks AI
Inference platform for open models: per-token serverless with Standard, Priority and Fast modes, batch at half the serverless price, on-demand GPUs billed per second, and LoRA or full fine-tuning (SFT, DPO) with tuned models served at the base price. Serverless embedding models too, from Qwen3 Embedding 8B to small BERT-size models. OpenAI-compatible.
Google Cloud Gemini Tuning
Google Cloud's managed fine-tuning for Gemini in Gemini Enterprise Agent Platform, formerly Vertex AI: supervised fine-tuning on Gemini 3.5 Flash, 3.5 Flash-Lite, 3.1 Flash-Lite and the 2.5 models, preference tuning on 2.5 Flash and Flash-Lite, and RL fine-tuning with up to 16 reward functions on 3.5 Flash and 3.1 Flash-Lite. From $1.50 per million training tokens on 2.5 Flash-Lite. Gemma, Llama and Qwen open models tune too.
Tinker (Thinking Machines)
Thinking Machines' fine-tuning API for open-weight models from 4B to 1T parameters: write the training loop in Python on your own machine with forward_backward, optim_step and sample, and Tinker runs it on its GPUs. LoRA only, for SFT, RL, DPO and distillation. Pay per token, from $0.396 per million training tokens, and download any saved checkpoint.
Together AI
Serverless API for open models such as gpt-oss, GLM and Kimi, OpenAI-compatible and billed per token, with batch, provisioned throughput, dedicated endpoints, fine-tuning (LoRA or full, SFT and DPO, priced per training token) and GPU clusters when you outgrow shared capacity. Image generation models too, such as FLUX.2, GPT Image 2 and Nano Banana Pro, priced per image. Video generation models as well, such as Seedance 2.5, HappyHorse and Hailuo 02.
Unsloth
Open-source fine-tuning library and desktop app for your own GPU or a free Colab notebook: LoRA, QLoRA, full fine-tuning, GRPO, DPO and FP8 for LLMs, vision, TTS and embedding models, which Unsloth says train 2x faster with 70% less VRAM. Exports to GGUF. Core Apache-2.0, Studio UI AGPL-3.0; Windows, Linux and macOS.