Reelsaw vs OpenShorts
Reelsaw vs OpenShorts: fully local, and any model you want
Reelsaw exists for two reasons: the whole pipeline should run on your own hardware with no API key, and every model in it should be swappable for any vendor. OpenShorts is the other open-source clipper, and it gets most of the way there: MIT core, Docker Compose, an MCP server, and an OpenAI-compatible option for moment picking. But its README says Gemini is still required for layout picking and for silent videos, so a key and a Google account stay in the loop.
OpenShorts is wider: dubbing, AI UGC videos, a YouTube studio, publishing, a hosted tier. Reelsaw is deeper on the thing both tools are for, turning long video into good clips: how moments are ranked, how filler cuts are verified, what the editor can override, and how a shared install runs. If the core capability and control over it are what you are choosing on, Reelsaw is the stronger pick; the rest of this page shows why, and where OpenShorts wins instead.
Pricing checked 2026-10-18 on each vendor's public page. Vendors change plans without notice; verify before you buy.
What OpenShorts costs
Both are free to self-host. OpenShorts also sells a hosted version.
What Reelsaw costs for the same job
The software is free under the AGPL-3.0 and there is no hosted plan to upsell you to. What you pay for is the machine it runs on and, only if you choose cloud models, the per-call price of those models.
Fully local: Ollama for the language model and Speaches (Whisper) for transcription. The installer picks a model by GPU memory or RAM (qwen2.5:14b with 24 GB of RAM or a 12 GB GPU, qwen2.5:7b from 12 GB, gemma3:4b below that), reuses one Ollama already has, and puts both on an NVIDIA GPU when there is one. Nothing leaves the box and there is no per-minute cost at all.
With cloud models: set OpenAI, Anthropic, Google, Groq, Deepgram, AssemblyAI or any OpenAI-compatible endpoint as a provider:model string and you pay that vendor's metered price for transcription minutes and a few thousand tokens of selection per video. There is no Reelsaw margin on top.
OpenShorts vs Reelsaw, feature by feature
What OpenShorts does better
- Breadth beyond clipping: voice dubbing, AI UGC videos with lip-synced actors, a YouTube title and thumbnail studio, and one-click publishing.
- A hosted option for people who do not want to self-host, with a GPU behind it.
- An optional Parakeet transcription backend (NVIDIA NeMo), about twice as fast as Whisper on the same card.
- A larger community: about 6.8k GitHub stars when checked.
Which one should you pick?
Pick OpenShorts if
- You want dubbing, UGC generation or direct publishing from the same tool.
- You might use the hosted version some months and self-host on others.
- You prefer a Python stack to extend.
Pick Reelsaw if
- No API key, ever: the one-command installer sets up Ollama and a local Whisper, and alignment and face detection run on-device. OpenShorts cannot drop Gemini.
- Any provider for any model, separately: transcription from Deepgram and selection from Anthropic, or everything from one OpenAI-compatible server, switched at runtime by an admin without a restart.
- Selection you can audit: every candidate is scored as the median of several samples, the top picks are compared pairwise with positions swapped to cancel judge bias, a separate judge model can do the scoring, and the rubric breakdown is one click away. OpenShorts asks Gemini for 3 to 15 moments in one pass.
- Filler, repetition and false-start cuts located by forced alignment and checked by listening to the seam, each one reviewable. OpenShorts does not list this.
- Framing decided per segment, not per video: face, split, stack and fit can change inside one clip at scene cuts, with active-speaker following, and any section can be overridden in the editor.
- A real editor: multi-lane timeline, frame-accurate trims, layout sections, transitions, intros and outros, undo.
- Built for more than one person: accounts, admin approval, per-user quotas, usage, and pg-boss jobs that resume after a crash.
- AGPL-3.0, so a hosted fork has to share its changes.
Common questions
Can OpenShorts run fully offline without any API key?
- Not according to its README on 2026-10-18: moment picking can use a local OpenAI-compatible server, but Gemini is still needed for layout picking and for silent videos. Reelsaw runs the whole pipeline locally with Ollama and a local Whisper, which is what its installer sets up by default.
Can I use Anthropic, OpenAI or Groq with each tool?
- Reelsaw: yes, each of the language, transcription and alignment models is a provider:model string, so you can mix vendors or go fully local, and admins can change them at runtime. OpenShorts: an OpenAI-compatible server can replace Gemini for moment picking; the other Gemini-backed steps stay on Gemini.
Which one picks better clips?
- Reelsaw does more work to find out: chunking at pauses with overlap so long videos do not lose their middle, rubric scores as a median of several samples, pairwise comparison of the top ten with swapped positions, an optional separate judge model, and a run-relative gate instead of a fixed count. OpenShorts asks Gemini for 3 to 15 moments in one pass. Neither project publishes a head-to-head benchmark, so try both on your own video.
Which is more open: MIT or AGPL-3.0?
- MIT lets anyone, including a company, take the code private and sell it as a service. AGPL-3.0 allows everything MIT allows except that: if you run a modified Reelsaw for other people, you must publish your changes. OpenShorts' core is MIT and its cloud directory is under a separate commercial licence; all of Reelsaw is AGPL-3.0.
Do both use an NVIDIA GPU?
- Yes, and for the same three jobs. OpenShorts builds one image with a GPU flag: faster-whisper on CUDA, NVENC encoding, and its detection models. Reelsaw adds a Compose override (docker-compose.gpu.yml) that hands the card to the Speaches container (faster-whisper on CUDA with large-v3), to Ollama when it runs in a container, and to the app, whose ffmpeg then encodes with NVENC; its face, text and alignment models stay on the CPU by default because they are small enough that the GPU did not measure faster. Neither runs CUDA inside Docker on a Mac; there, Reelsaw's installer runs Ollama natively on Metal.
Do both have MCP servers?
- Yes. Both can be driven from Claude Code, Claude Desktop, Cursor or a script. OpenShorts also has a REST API with webhooks and a pip-installable CLI; Reelsaw's CLI is an operator tool inside the container, and its MCP server can use OAuth so claude.ai connectors sign in through the browser.
Related comparisons
Sources
Last updated 2026-10-18.