AI tool comparison
Gemma Tuner Multimodal vs Pretty Fish
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
Gemma Tuner Multimodal
Fine-tune Gemma 4 with audio + vision on Apple Silicon — no NVIDIA needed
75%
Panel ship
—
Community
Free
Entry
Gemma Tuner Multimodal is an open-source fine-tuning toolkit for Google's Gemma 4 and Gemma 3n models that runs entirely on Apple Silicon using PyTorch with Metal Performance Shaders (MPS) backend — no NVIDIA GPU or cloud infrastructure required. It supports LoRA training on multimodal inputs: audio, images, and text simultaneously, using local CSV files or streamed from Google Cloud Storage or BigQuery. The tool targets the growing segment of developers who own M-series Macs but have been locked out of fine-tuning workflows that assume CUDA availability. Gemma 4's architecture is particularly well-suited to this use case: its 4B multimodal variant (designed for on-device deployment) trains efficiently on M3 Max and M4 Pro hardware within the available unified memory constraints. Primary use cases include medical transcription fine-tuning (audio → text with clinical terminology), visual QA systems (image + text → structured response), and private on-device pipelines where cloud API calls are prohibited by compliance requirements. The project fills a specific niche that Google's own fine-tuning documentation doesn't cover well for Apple hardware.
Developer Tools
Pretty Fish
Free, beautiful Mermaid diagram editor that works offline
75%
Panel ship
—
Community
Free
Entry
Pretty Fish is a free, open-source Mermaid diagram editor with live preview, 5 built-in themes, multi-page workspaces, and one-click SVG/PNG export. It works offline as a Progressive Web App (PWA) and requires no account, no login, and no installation. It supports all 14+ Mermaid diagram types including flowcharts, sequence diagrams, Gantt charts, entity-relationship diagrams, and Git graphs. The editor includes syntax highlighting, auto-completion, instant error feedback, and a clean split-pane layout. The multi-page workspace lets you manage entire diagram projects in a single session. Export quality is excellent — SVG output is clean and scaling-ready for use in presentations, docs, or design systems. Pretty Fish hit Hacker News front page today with 128 points and has the makings of the go-to Mermaid editor for developers who generate diagrams from AI-assisted documentation workflows. With LLMs increasingly generating Mermaid syntax in their outputs, having a polished renderer and editor matters more than ever.
Reviewer scorecard
“Finally something that treats Apple Silicon as a first-class fine-tuning target, not an afterthought. LoRA on Gemma 4 multimodal for domain-specific tasks — medical, legal, private enterprise — is a genuinely underserved workflow. This is the tool the community needed.”
“The official Mermaid live editor is clunky and slow. Pretty Fish loads instantly, works offline, and the multi-page workspace means I can manage all my architecture diagrams in one place. Bookmarking this immediately as my default Mermaid editor.”
“MPS backend for fine-tuning is still meaningfully slower than CUDA for most workloads, and Gemma 4's multimodal capabilities are weaker than the top closed models. For production use cases, you'll still want a cloud GPU for the training run even if you deploy locally after.”
“It's a genuinely nice editor but it's solving a niche problem — most devs who need Mermaid diagrams already use VS Code extensions or embed them in Notion. And with no backend, there's no collaboration or sharing story, which limits its use in team workflows.”
“The laptop-as-AI-training-cluster future is closer than most think. Apple's Neural Engine roadmap has MPS compute doubling every 18 months. Fine-tuning workflows that work on today's M4 Pro will run on tomorrow's M5 in an hour instead of overnight.”
“As AI tools increasingly output Mermaid syntax to explain architectures and flows, the need for a great rendering environment grows. Pretty Fish positions itself at the intersection of AI-generated diagrams and human editing — that's a well-timed niche.”
“Being able to fine-tune a model on my own creative portfolio and voice without sending my work to a cloud provider is a privacy game-changer. Custom style models trained locally, owned fully — this is the future of personalized creative AI.”
“Five beautiful themes and clean SVG exports mean I can finally use Mermaid diagrams in client-facing presentations without them looking like developer scratch notes. This is the Mermaid editor I've always wanted and the zero-friction setup seals it.”
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