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Soup CLI vs TheySaid 3.0: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Soup CLI and TheySaid 3.0 — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

S

Soup CLI

MePlay, Inc.

Free

Open-source CLI that runs the whole LLM post-training stack — SFT, DPO, ORPO — on a 4GB laptop GPU.

Key features

  • Whole Post-Training Stack: SFT, DPO, ORPO, SimPO, KTO, and more in one CLI.
  • Low-VRAM Streaming: Fine-tune Llama-3.1-8B on a 4 GB GPU by streaming the base from RAM/NVMe.
  • Auto-Configured Runs: Task, LR, epochs, and quantization derived from rules instead of grid search.
  • Self-Healing Training: Detects and self-corrects reward hacking mid-run.
  • One-Command Migration: `soup migrate` converts LLaMA-Factory, Axolotl, and Unsloth configs.
  • Ship Gate: Every checkpoint is evaluated and either passes or is rejected before saving.
  • Broad Ecosystem: Integrates with HuggingFace, Ollama, vLLM, DeepSpeed, Unsloth, ONNX, TensorRT, W&B.
  • MLX + Apple Adapter: First-class Apple silicon support.

Best for

  • Fine-tuning open-source LLMs on a consumer laptop GPU
  • Post-training alignment (DPO/ORPO) without a rented A100
  • Migrating existing LLaMA-Factory / Axolotl pipelines to a simpler workflow
  • Producing evaluated, ship-gated checkpoints for internal deployment
  • Researchers experimenting with 23 training methods without rewriting scripts
View Soup CLI details
TheySaid 3.0 logo

TheySaid 3.0

TheySaid

Freemium

Turn single-question surveys into real-time conversational surveys to boost engagement and surface richer insights.

Key features

  • Conversational Survey Conversion: Transforms single-question surveys into AI-driven multi-turn conversations that probe respondents with contextual follow-ups to gather richer qualitative data.
  • Real-time Engagement: Dynamically adapts follow-up prompts based on answers to keep respondents engaged and reduce drop-off during the survey experience.
  • Automated Insight Extraction: Aggregates and summarizes responses, surfaces recurring themes and sentiment, and highlights actionable findings for faster analysis.
  • Intelligent Question Generation: Generates clarifying and targeted follow-up questions tailored to each respondent’s answers to obtain deeper context and reasons.
  • Response Analytics Dashboard: Provides aggregated views, filters, and breakdowns (e.g., sentiment and themes) to help teams interpret results quickly.
  • Export & Integration: Enables exporting response data and integrating survey outputs with downstream analytics or research workflows for further analysis.
  • Conversational AI Surveys that adapt follow-up questions based on responses
  • AI Interviews to automate in-depth user interviews
  • AI Pulses and Polls for single-question feedback and follow-ups
  • Question recommendation and auto-generation from website content
  • Embedding and delivery via existing channels
  • AI-driven summarization of responses and insights
  • Convert single-question surveys into interactive, AI-driven conversations
  • Real-time capture of conversational survey responses
  • Smart conversational survey design to boost respondent engagement
  • Automated analysis and extraction of insights from conversational responses
  • Web-based survey creation and results dashboard

Best for

  • Converting NPS/CSAT single-question prompts into conversational flows to collect reasons, suggestions, and context behind scores for better actionability.
  • Market research that requires scalable qualitative feedback by turning short surveys into richer interviews to surface customer needs and motivations.
  • Customer support and feedback collection that triages issues via guided conversation and captures exact user language and sentiment for product teams.
  • Employee pulse and HR surveys that solicit candid explanations and suggestions while maintaining higher completion rates through conversational engagement.
  • Product discovery and usability testing to gather in-depth user reactions, feature requests, and pain points from compact, conversational surveys.
  • Collecting product and UX feedback via conversational surveys
  • Automating user interviews to surface deeper insights
  • Running NPS/CSAT/CES pulses with follow-up probing
  • Embedding surveys across websites and apps to increase engagement
  • Conducting user tests and polls with AI follow-ups to understand reasons
  • Customer feedback collection with richer qualitative responses
  • Market research using conversational probes to uncover insights
  • Product feedback and user experience surveys
  • NPS and satisfaction measurement with follow-up conversational context
  • Employee engagement and pulse surveys
View TheySaid 3.0 details