Open-weight chat models are now good enough to run meaningful creative work locally: outlining scripts, generating shot lists, rewriting dialogue, checking tone, and doing structured “review passes” before you ever hit export. For Reactivid-style pipelines, the two things that matter most are (1) predictable instruction-following and (2) license clarity so you can ship without surprises.
This list is intentionally constrained to models with permissive licenses (Apache 2.0 or MIT) that you can download and run locally. That excludes several popular “open weight” families that use bespoke terms, non-commercial clauses, or other restrictions.
How we ranked these (practical, not academic)
We prioritized:
- English output quality for chat, rewriting, and instruction-following
- Reliability with structured outputs (bullets, JSON-ish blocks, consistent sections)
- Local deployability (good community tooling, quantizations, common runtimes)
- License clarity (Apache 2.0 or MIT on the model listing)
A note on “best”: model quality depends heavily on prompts, decoding settings, and quantization level. Treat this as a production short-list, not a universal truth.
Quick recommendations (pick fast)
- Best overall quality-per-compute (general creative work): Mixtral 8x7B Instruct :contentReference[oaicite:0]{index=0}
- Best “bigger swing” quality (if you can afford VRAM): Mixtral 8x22B Instruct :contentReference[oaicite:1]{index=1}
- Best strong generalist in a dense mid-size (great long-context workflows): Qwen2.5 14B Instruct :contentReference[oaicite:2]{index=2}
- Best small model that still feels “serious”: Phi-3.5 Mini Instruct :contentReference[oaicite:3]{index=3}
- Best for “fully open training lineage” and transparent releases: OLMo Instruct line :contentReference[oaicite:4]{index=4}
Top 10 permissive, local-first chat models (ranked)
1) Mixtral 8x7B Instruct (Apache 2.0)
Mixtral 8x7B remains one of the most consistently useful open models for real creative workflows: ideation, rewrites, structured outlines, and multi-step instruction following. Mistral released it under Apache 2.0 and positioned it as a cost/performance leader. :contentReference[oaicite:5]{index=5}
Best for: script drafts, segment outlines, alternate hooks, “rewrite in X style,” and batch prompt workflows.
Why it ranks here: strong instruction-following, good tone control, and excellent output for the compute.
2) Mixtral 8x22B Instruct (Apache 2.0)
When you want a noticeable bump in response quality (better composition, fewer “template-y” answers, stronger multi-paragraph coherence), Mixtral 8x22B Instruct is a strong permissive option—at the obvious cost of heavier hardware requirements. :contentReference[oaicite:6]{index=6}
Best for: long-form outlines, narrative continuity, higher-stakes copy, and deeper planning passes.
Operational note: this is large; plan around VRAM and/or aggressive quantization.
3) Qwen2.5 14B Instruct (Apache 2.0)
Qwen2.5’s instruct models are practical and robust for “content factory” style work: structured outputs, checklist generation, and consistent formatting. Qwen’s blog and Hugging Face listings indicate Apache 2.0 for most of the open models in the family (with exceptions called out by Qwen). :contentReference[oaicite:7]{index=7}
Best for: structured scripting (sections, beats, timing notes), prompt templates, and long-context review tasks.
Why it’s a staple: strong instruction-following and very usable long-context workflows.
4) Mistral 7B Instruct (Apache 2.0)
Mistral 7B is still a baseline workhorse: fast, capable, and easy to deploy broadly. Mistral explicitly released Mistral 7B under Apache 2.0. :contentReference[oaicite:8]{index=8}
Best for: fast iteration, short edits, headline variants, and “good enough” assistant behavior on commodity hardware.
Why it stays relevant: low friction and reliable outputs at small scale.
5) OLMo-3.1 32B Instruct (Apache 2.0)
If you care about open training lineage and the ability to reason about a model’s provenance and release practices, the OLMo line is worth attention. Ai2’s OLMo instruct releases are listed under Apache 2.0. :contentReference[oaicite:9]{index=9}
Best for: higher-quality drafting and review passes where “fully open” matters.
Practical angle: a 32B-class model is heavier than most local setups, but it’s a serious option if you have the box.
6) OLMo-3 7B Instruct (Apache 2.0)
A smaller sibling that still benefits from the OLMo ecosystem and approach, OLMo-3 7B Instruct is explicitly listed under Apache 2.0. :contentReference[oaicite:10]{index=10}
Best for: “open-first” shops that want a lighter model for daily assistant tasks.
Where it shines: dependable behavior for templated writing and structured planning prompts.
7) Phi-3.5 Mini Instruct (MIT)
Phi models are attractive when you want a small model that still feels competent in production. Microsoft’s Phi-3.5 Mini Instruct is listed under the MIT license. :contentReference[oaicite:11]{index=11}
Best for: on-device assistants, fast “writer’s room” iterations, and helper tasks embedded into tooling.
Workflow fit: great as the “draft + format” model that feeds a heavier model only when needed.
8) IBM Granite 3.2 8B Instruct (Apache 2.0)
Granite instruct models are positioned for practical assistant behavior, and the Granite 3.2 8B Instruct listing specifies Apache 2.0. :contentReference[oaicite:12]{index=12}
Best for: businesslike writing, structured outputs, and consistent tone in product content.
Why include it: a solid mid-sized option with clear licensing and a “professional assistant” vibe.
9) MPT-30B Instruct (Apache 2.0)
MPT is older relative to today’s top performers, but it’s still useful—especially if you already have MPT tooling in place. The model listing states Apache 2.0. :contentReference[oaicite:13]{index=13}
Best for: internal tools, legacy deployments, or teams that value stability and familiar behavior.
When it makes sense: controlled environments where “good enough + known” beats chasing the newest weights.
10) Qwen2.5 0.5B Instruct (Apache 2.0)
A small instruct model can be surprisingly valuable in a media workflow—think: metadata normalization, title variants, tag suggestions, and quick rewrites that don’t justify spinning up a larger model. Qwen2.5 0.5B Instruct is listed with an Apache 2.0 license. :contentReference[oaicite:14]{index=14}
Best for: lightweight automation steps inside pipelines (naming, formatting, short rewrites).
How to use it: as a “utility model” that runs constantly, with escalation rules to a larger model.
How these fit into Reactivid-style creative workflows
Here are three patterns that work well in practice:
-
Two-pass scripting
- Pass 1 (fast model): outline, structure, constraints, timing targets.
- Pass 2 (strong model): voice polish, style consistency, punchlines, transitions.
-
Deterministic “review passes” Use a fixed prompt and temperature for repeatable checks:
- clarity pass
- tone pass
- “remove claims / tighten language” pass
- compliance pass (for your own internal policies)
-
Structured outputs for downstream automation Even if you don’t demand perfect JSON, ask for stable sections:
- Hook
- Beat sheet
- Scene list
- VO script
- On-screen captions (short)
License hygiene (don’t skip this)
Even within permissive families, double-check:
- the exact model variant you’re downloading (base vs instruct vs community fine-tune)
- whether the license applies to weights (not just code)
- any special notes on hosted services vs local usage
For example, Qwen explicitly calls out license differences across some sizes/variants in the Qwen2.5 family—so confirm you’re on an Apache 2.0 model before shipping. :contentReference[oaicite:15]{index=15}
Closing recommendation
If you want one “default stack” to start building with today:
- Primary: Mixtral 8x7B Instruct
- Upgrade path: Mixtral 8x22B Instruct or Qwen2.5 14B Instruct
- Always-on utility: Phi-3.5 Mini Instruct or Qwen2.5 0.5B Instruct
That combination covers fast iteration, higher-quality drafts, and automation-friendly glue work—while keeping licensing permissive and straightforward. :contentReference[oaicite:16]{index=16}