# Fine-tuning developer tools

> 7 developer and vibe-coding tools tagged fine-tuning in the Digidle Tools directory, across categories, A to Z, each with its official link.

- Tag page: https://digidle.com/tags/fine-tuning/
- All tags: https://digidle.com/tags/

## Tools (A to Z, not a ranking)

- [Amazon Bedrock Model Customization](https://digidle.com/tools/bedrock-model-customization.md) (Frameworks & Dev Tools): 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. Official site: https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html.
- [Axolotl](https://digidle.com/tools/axolotl.md) (Frameworks & Dev Tools): 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. Official site: https://axolotl.ai.
- [Fireworks AI](https://digidle.com/tools/fireworks-ai.md) (Frameworks & Dev Tools): 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. Official site: https://fireworks.ai.
- [Google Cloud Gemini Tuning](https://digidle.com/tools/gemini-tuning.md) (Frameworks & Dev Tools): 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. Official site: https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/tuning.
- [Tinker (Thinking Machines)](https://digidle.com/tools/tinker.md) (Frameworks & Dev Tools): 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. Official site: https://thinkingmachines.ai/tinker/.
- [Together AI](https://digidle.com/tools/together-ai.md) (Frameworks & Dev Tools): 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. Official site: https://www.together.ai.
- [Unsloth](https://digidle.com/tools/unsloth.md) (Frameworks & Dev Tools): 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. Official site: https://unsloth.ai.

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Source: Digidle Tools (https://digidle.com/), a curated directory of developer and vibe-coding tools. Pricing is not verified by Digidle unless stated in a description; check the official site. Full index: https://digidle.com/llms.txt