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Scheduled launch — Aug 10, 2026

Soup CLI is listed on AI Kaptan and will enter the daily launch competition on that day. Community upvotes open on launch day.

Soup CLI
Developer Tools
Free

Soup CLI

Fine-tune an 8B LLM on a 4 GB laptop GPU using layer streaming. Single YAML configuration for SFT, DPO, GRPO, KTO, evaluation, quality gating, and export under the Apache-2.0 license.

Rating
0
Reviews
0
Upvotes
about 3 hours ago
Listed
Open Source
Developer Tools
Artificial Intelligence
LLM Fine Tuning
CLI
Machine Learning
Python
Tool information
Provider
Alpamys Makazhan
Platforms
Linux
macOS
Windows
Languages
English
Python
Added to directory
about 3 hours ago
Last updated
about 3 hours ago
Rating
Not available
Pricing
Free

About Soup CLI

What the tool does and who it's for

Soup CLI is an open-source post-training toolkit designed to fine-tune 8B parameter language models on consumer hardware with as little as 4 GB of VRAM. By utilizing layer streaming during LoRA fine-tuning, Soup keeps the frozen base model in system RAM or NVMe and streams decoder layers into GPU VRAM one layer at a time, bounding peak VRAM to a single layer. Configured via a single YAML file, Soup supports 23 post-training methods including SFT, DPO, GRPO, ORPO, SimPO, and KTO. It also includes pre-flight data diagnostics, automated quality gating, quantization support, and export tools under the Apache-2.0 open-source license.

Key capabilities

Layer Streaming Architecture: Streams frozen base model weights from RAM into VRAM one decoder layer at a time to drastically lower peak memory consumption.
8B Fine-Tuning on 4 GB VRAM: Enables fine-tuning 8-billion-parameter models like Llama-3.1-8B on entry-level laptop GPUs like the RTX 3050 4 GB.
Single YAML Workflow: Define data preparation, training, evaluation, gating, and export in a single configuration file.
Comprehensive Alignment Methods: Supports SFT, DPO, GRPO, KTO, ORPO, and SimPO without requiring extra memory for reference models.
Pre-flight Data Doctor: Detects dataset issues prior to training, including chat template formatting errors and EOS token bugs.
Automated Quality Gating: Evaluates models against derived benchmarks and enforces ship/don't-ship thresholds on model saves.
Quantization & Export: Supports 17 quantization formats including 4-bit NF4 quantization to maximize hardware efficiency.
Cross-Platform MLX Support: Integrates with PyTorch, CUDA, Hugging Face, and Apple MLX for native M1–M4 Apple Silicon acceleration.

Pricing

Free — plans below

Free / Open Source

Most popular

$0

  • 100% Free & Open Source
  • Apache-2.0 License
  • Full CLI access
  • Layer streaming engine
  • All 23 training methods

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