local-ai-code-assistant vs Poolside AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-01
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At a glance

Dimensionlocal-ai-code-assistantPoolside AI
PricingFree (open-source)Contact for pricing (enterprise)
DeploymentLocal desktop app, fully offlineOn-prem, VPC, workstation (defense only)
Model SupportedMultiple open-source models (Mistral, Llama, Phi, etc.)Custom Laguna models (XS.2, M.1) with 256K context
Target UserPrivacy-conscious individual developers & hobbyistsLarge enterprises in regulated industries (finance, healthcare, defense)
Key FeatureMulti-model side-by-side execution, offline privacyMulti-agent orchestration, 256K context, custom on-prem models
Collaboration & GovernanceNo collaboration features, fully localRole-based access control, auditability, executive governance

Choose local-ai-code-assistant if you're a solo developer who values privacy and zero cost, and want to run multiple open-source models offline. Choose Poolside AI if you're an enterprise in a regulated industry needing custom models, multi-agent orchestration, and on-prem deployment with full governance. They serve completely different needs.

Try local-ai-code-assistantTry Poolside AI
local-ai-code-assistant
local-ai-code-assistant

CodeLoom is a free, open-source desktop app that runs multiple local LLMs side by side as separate coding threads on your own machine.

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Poolside AI
Poolside AI

Open-weight agentic coding models — Laguna XS 2.1 (33B) and Laguna S 2.1 (118B) — built for code that cannot leave your security boundary.

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Pricing
Free
Contact Sales
Plans
$0
—
Popularity
6 views
7.1k views
Skill Level
Intermediate
Advanced
API Available
Platforms
Desktop
DesktopCLIAPIWeb
Categories
💾 Local & On-Device AI💻 Code & Development
💻 Code & Development🛠️ Autonomous Coding Agents⚛️ Foundation Models & LLM APIs🛡️ AI Governance & Guardrails
Features
Multi-Weave architecture: up to five concurrent model sessions in one workspace
Contextual Thread Fusion: pass output from one model thread into another without copy-paste
Universal Model Manager: import from Hugging Face, Ollama, or local GGUF/GPTQ files
Automatic quantization selection (4-bit, 8-bit, FP16) based on VRAM and RAM
Native File Looming: indexes project directories up to 100k tokens and slices them across threads
Intelligent Prompt Looms: reusable templates that distribute one instruction across multiple models
Documented "Code Review" loom: security, performance, and style analysis in one click
Local inference backends: llama.cpp, ExLlama, MLX
Fast weft path: 1–3B models respond in under 200ms for autocomplete and linting
Warp thread path: 7–70B models for refactoring, explanation, and design decisions
Per-thread context windows, conversation history, and parameter sets you can pause, kill, or redirect
Real-time collaborative editing over a local WebSocket with no internet required
Fully offline operation: no telemetry, no cloud relays, no user accounts
Cross-platform desktop client: Windows x64, macOS (Apple Silicon + Intel), Linux x64/ARM
Multilingual interface in 12 languages including English, Spanish, Mandarin, Japanese, Korean
Laguna S 2.1 open-weight model: 118B params, 8B active, 1M context
Laguna XS 2.1 open-weight model: 33B params, 3B active, 256K context
Laguna XS 2.1 sized to run on-device for lightweight scenarios
Laguna S 2.1 positioned for frontier-class long-horizon reasoning
Single-agent and multi-agent orchestration with planning and tool use
Sandboxed agent execution environments for running generated code safely
Desktop app and CLI for agentic coding sessions
VS Code and Visual Studio extensions (per Poolside blog)
macOS desktop assistant (per Poolside blog)
Model selection, tool grouping, and project management in the client
Always-ask approval mode before edits are accepted
Data connectors to repositories, databases, and warehouses
Role-based access control for both human users and agents
End-to-end trace observability for agent runs
Governance and auditability built for regulated environments
Integrations
Hugging Face
Ollama
OpenRouter
Vercel AI Gateway

What real users say: local-ai-code-assistant vs Poolside AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

local-ai-code-assistant

30 mentions across 2 sources · 65% positive (averaged across 2 sources)

YouTube, GitHub

What users praise

  • • Privacy-first: code never leaves your machine, essential for regulated industries.
  • • Multi-model support: assign different models to tasks like autocomplete or refactoring.
  • • Offline capability: works 24/7 without internet, no server dependencies.
  • • Free and open-source: no subscriptions or hidden costs, full control.

What frustrates them

  • • Hardware intensive: large models need high VRAM, limiting accessibility.
  • • Early-stage: few stars and limited community means immature ecosystem.
  • • Setup complexity: multi-model and backend configuration has a learning curve.
  • • No cloud-level intelligence: local models may underperform GPT-4-class in tasks.

Researched Aug 7, 2026

Poolside AI

40 mentions across 4 sources · 48% positive — mixed (averaged across 4 sources)

Hacker News, YouTube, Bluesky, Lemmy

What users praise

  • • Open-weight models with strong SWE-bench scores (72.5%).
  • • On-prem, VPC, and air-gapped deployment for high security.
  • • 256K context length supports long-horizon reasoning tasks.
  • • Multi-agent orchestration with sandboxed execution environments.

What frustrates them

  • • Community feedback is scarce; limited real-world user reviews.
  • • Platform is still in research preview as of April 2026.
  • • Pricing is opaque; only 'contact us' with no published tiers.
  • • Trademark dispute with Poolside FM creates name confusion.

Researched Jul 17, 2026

Who should pick which

  • Solo founder working on a side project with sensitive code
    Pick: local-ai-code-assistant

    Free, fully offline, runs on personal laptop with multiple open-source models; no data leaves the machine.

  • Enterprise development team in a bank needing AI for complex legacy code
    Pick: Poolside AI

    Custom on-prem models, 256K context for long tasks, role-based access control, and auditability.

  • Hobbyist experimenting with different local LLMs
    Pick: local-ai-code-assistant

    Supports many open-source models side-by-side for free, no setup beyond desktop app.

  • Healthcare company deploying AI inside a secure VPC
    Pick: Poolside AI

    On-prem or VPC deployment, custom foundation models, and governance features meet regulatory needs.

  • Open-source contributor wanting offline autocomplete
    Pick: local-ai-code-assistant

    Free, offline, and integrates locally without subscription.

Frequently Asked Questions

local-ai-code-assistant vs Poolside AI: which should you choose?

Choose local-ai-code-assistant if you're a solo developer who values privacy and zero cost, and want to run multiple open-source models offline. Choose Poolside AI if you're an enterprise in a regulated industry needing custom models, multi-agent orchestration, and on-prem deployment with full governance. They serve completely different needs.

Can I use local-ai-code-assistant without internet?

Yes, it operates fully offline; models run locally.

Does Poolside AI require internet?

No, it can be deployed on-prem or in a VPC, enabling air-gapped operation.

What models does local-ai-code-assistant support?

Multiple open-source models like Mistral, Llama, Phi, etc.

What models does Poolside AI use?

Custom Laguna XS.2 (33B params, 3B active) and M.1 (225B params, 23B active) with 256K context.

Is local-ai-code-assistant free?

Yes, it is free and open-source.

How much does Poolside AI cost?

Pricing is not public; contact sales for enterprise quotes.

Which tool is better for privacy?

local-ai-code-assistant ensures no data leaves your machine. Poolside also offers on-prem deployment for privacy.

Can Poolside AI handle long multi-step tasks?

Yes, with 256K context and multi-agent orchestration, it excels at long-horizon planning.

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Explore each tool further

local-ai-code-assistant
View local-ai-code-assistant reviewlocal-ai-code-assistant alternatives
Poolside AI
View Poolside AI reviewPoolside AI alternatives

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Best AI Local & On-Device AI toolsBest AI Code & Development toolsBest AI Autonomous Coding Agents toolsBest AI Foundation Models & LLM APIs tools
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Last reviewed: July 1, 2026