product update

Perplexity Computer now runs fully on-device on Macs with 36GB+ RAM, using Qwen 3.6 or PPLX Pro

TL;DR

Perplexity now lets users run its entire Computer experience, including the harness and orchestrator, locally on Apple Silicon Macs with at least 36GB of RAM. Users can choose Qwen 3.6 or PPLX Pro, a Perplexity post-trained Qwen 3.6 variant. The feature is available today to Pro, Max and Enterprise subscribers.

3 min read
0

Perplexity has made it possible to run its full Computer experience, including the harness and orchestrator, entirely on a user's own Mac. The requirement is a recent Apple Silicon machine with at least 36GB of RAM. The feature is available starting today (Oct. 20, 2026) to Perplexity Pro, Max and Enterprise subscribers, Engadget reports.

What's new

In early September, Perplexity introduced Hybrid Compute, an update to its Computer app that split AI workloads between frontier models and local models running on the user's machine. Today's release goes further: the agent harness and orchestrator now run on-device too, so a task can run end to end without leaving the Mac.

Users can pick one of two local models:

  • Qwen 3.6, the open model from Alibaba's Qwen team.
  • PPLX Pro, a Perplexity offshoot of Qwen 3.6. According to Perplexity, the company did its own post-training on it to tune it for Computer use.

Parameter counts, context window and benchmark results for either local configuration were not disclosed in the announcement as reported.

Privacy and cost claims

Perplexity pitches the feature on data control and credit spend. Its example: with access to the Notes and Mail apps, Computer can generate a prioritized to-do list without any email data being sent to the cloud. The company says: "As more demanding workflows become practical to run locally, the machines people already own will take on a larger share of their AI work. This gives users more control over sensitive data and credit spend."

These are Perplexity's claims. No independent testing of local task quality, speed or privacy guarantees has been published.

Frontier escalation and sandboxing

Local mode is not strictly offline-only. If a task would benefit from a stronger model, users can authorize Computer to call one of more than 15 frontier models. Any code or tool execution a task requires runs in an isolated sandbox. Perplexity says these security protocols are the same ones used in the cloud version of Computer.

Availability and setup

  • Plans: Pro, Max and Enterprise.
  • Hardware: Apple Silicon Mac with at least 36GB of RAM.
  • Setup: Install the latest Perplexity Mac app, then follow the in-app instructions to download and install a local model.
  • Pricing: No separate fee for local mode was disclosed. Subscription pricing was not part of the announcement.

What this means

The 36GB RAM floor is the main constraint. It excludes base-configuration Macs and limits local mode to higher-memory machines, so the feature will reach only a subset of Perplexity's Mac users. That floor also indicates how much memory a capable agentic stack needs once the model, the orchestrator and the working context all sit on one device.

Strategically, Perplexity is building on an open-weight base (Qwen 3.6) and differentiating through post-training and its harness rather than pretraining. PPLX Pro follows that pattern. The open question is how large the quality gap is between local models and the frontier models Computer can escalate to. Perplexity has published no data on it, and that gap will determine how many tasks users actually keep on-device.

The privacy argument is real for tasks touching local mail and notes. But because the cloud-escalation option stays available, the actual data exposure depends on how often users authorize it and on what context gets passed along. Perplexity has not detailed that.

Related Articles

product update

Google releases free AI Edge Foresight, a Mac note-taking app that transcribes meetings fully offline

Google has released AI Edge Foresight, a free experimental macOS app that transcribes meetings and audio files entirely on-device. It is optimized for Apple Silicon Macs and uses Google's EmbeddingGemma 2 model, according to The Verge. Google says audio, files, and notes never leave the user's computer.

product update

Liquid AI Publishes GGUF Builds of LFM2.5-24B-A2B, Including a 13.6 GB Quantization-Aware Q4_0 Checkpoint

Liquid AI has published GGUF builds of LFM2.5-24B-A2B, a 24B-parameter model on the lfm2moe architecture, in sizes from 13.6 GB (Q4_0) to 48 GB (BF16). The Q4_0 file is a Quantization-Aware Distillation checkpoint trained to recover accuracy lost to 4-bit quantization.

product update

Google builds Antigravity into Gemini app for macOS, limited to AI Ultra subscribers

Google has integrated Antigravity, its agent-first development platform, directly into the Gemini app for macOS as part of the Gemini 4 Argon rollout. Access requires an AI Ultra subscription, while the new model itself requires AI Pro or above. The update also renames and reorganizes several app features, including Gemini Spark, Skills and Connectors.

product update

NVIDIA releases 96 GiB NVFP4 build of Qwen3.8-Flash-Next for single-GPU Blackwell and DGX Spark

NVIDIA has published Qwen3.8-Flash-Next-FP4-Local, a 96 GiB NVFP4 quantization of Alibaba's 125B-parameter MoE model, on Hugging Face. NVIDIA reports 91.5% on GPQA Diamond versus 92.2% for BF16. It requires NVIDIA's custom vLLM containers because upstream support has not landed.

Comments

Loading...