Local-first coding for Apple Silicon

Your local model
can build more.

Kynd Code is not a cloud coding agent with a localhost setting. Its agent loop, tool choices, context handling and inference servers are designed around the models that actually fit on your Mac.

No API key No account 30 days fully open Your code stays local
Real Kynd Build interface

Explore → edit → verify → preview

Improve the local model picker
ChatBuild
LSP Ornith 1.0 9BMLX ToolsAuto Workbench
Make the local model picker explain which model fits this Mac and why.
I'll trace the current picker, then make the smallest safe change.
▣ Todo List1/4
Find the model profile and picker code
2Add the fit explanation to each card
3Check diagnostics and targeted tests
4Open the updated interface in Preview
code searchModelPicker · config.js · 14 matchesdone
The picker already receives the calibrated memory tier. I can explain the recommendation without adding another service.
edit filesrc/ModelPicker.tsx · +18 −3done
+ const fit = profile.memoryTiers.find(+  tier => ramGb >= tier.minRamGb+ )
LSP diagnosticsModelPicker.tsx0 errors
›_bashnpm test -- model-picker8 passed
Previewlocalhost:4173ready
Done. Each model now explains its memory fit, backend and context allowance before you load it.
▢ AutoReasoning Standard⚡ GeneralWorkflow⌃
Ask anything… drop files here.
Live Preview
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function ModelCard({ profile, ramGb }) {
  const fit = selectMemoryTier(profile, ramGb)

  return (
    <article className="model-card">
      <strong>{profile.name}</strong>
      <FitNote tier={fit} />
    </article>
  )
}
Kynd models

Recommended for this Mac

O
Ornith 1.0 9BBest agentic fit for 16 GB unified memory
Selected
Q
Qwen3.6 35B A3BNeeds 32 GB · 65K calibrated context
Details
Calibrated on this Mac · 31.8 tok/s
Activity⌘ Agent›_ Shell
Searching project symbols…
Your modelKynd inferenceFocused agent loopFiles + LSPLive Workbench

One private system. One Mac. No code sent to a cloud model.

The difference

Local support is a checkbox.
Local-first is an architecture.

Pointing a cloud-era coding harness at localhost does not remove its cloud-era assumptions. Kynd Code changes the agent and the inference layer together.

Generic local endpointmodel adapts to the agent
01

Every tool, every turnLarge schemas consume context before useful work begins.

02

Full history, re-prefilledLong sessions make a small local server feel progressively heavier.

03

One prompt fits every modelQuant, architecture and memory constraints are left to you.

“It connects” is where the optimisation stops.
Kynd Codeagent adapts to the model

Focused tool surfaceTen essential coding tools, discovery, and only the extras the task needs.

Conversation and prefix cachesReuse work already prefetched instead of paying for it again.

Per-model runtime profilesSampling, context, backend and cache strategy follow the actual model and Mac.

Built for the constraints that make local AI local.

Why not just use localhost?

OpenCode and Cline can connect to local models.
Kynd Code starts there.

Generic agents are useful and their capabilities change quickly. This comparison is about Kynd Code’s design focus—not a benchmark of another product release.

Design decisionGeneric agent + local endpointKynd Code
Primary targetCloud-scale models, with local providers availableModels that fit in unified memory
Tool surfaceBroad harness presented to the modelCompact essentials + task discovery
Context reuseDepends on the connected providerFork and prefix caching inside Kynd’s server
Mac fitChoose and tune the server yourselfCalibration, benchmark match and RAM-aware profiles
VerificationTerminal and editor integrations varyLSP checks, live Preview and browser tools in one Workbench
LearningSession or provider dependentLocal error→fix patterns can be reused without inference

Agent build × Website Studio

One prompt builds it.
Then shape it instantly.

Ask Kynd to create the website in Build. Once the structure is there, open the real page in Website Studio and handle the human details yourself—change a line, try a colour, add a button or move a section without asking the model to start another turn.

No repeat prompt No model round-trip Writes back to source
Prompt-only workflowSmall change, full loop
  1. 01
    “Build me a landing page.”Agent finds files, writes code, renders.
    wait
  2. 02
    “Change that headline.”Agent finds the same component again.
    wait
  3. 03
    “Try a warmer green.”Another prompt, patch and render.
    wait
  4. 04
    “Add one line above the button.”Another model turn for a tiny edit.
    wait
4 model turns

Context and time spent repeating simple visual instructions.

Kynd Code workflowBuild once, shape directly
  1. 01
    “Build me a landing page.”Kynd plans, codes, checks and previews it.
    agent
  2. 02
    Click the headline. Type the words.The canvas changes as you type.
    instant
  3. 03
    Pick a colour in Design.See it on the real page immediately.
    instant
  4. 04
    Add an element. Press Save.The edited HTML writes back to the project.
    source
1 model turn

Visual follow-up work stays fast, local and under your hand.

01 · Ask the agent “Build a welcoming private-AI homepage.”

Kynd creates the files, checks the page and opens it in the Workbench.

Agent build
Website Studio Visualindex.html
Fluid
All changes saved
body › main › section.hero
PRIVATE BY DESIGN

Local AI,
made friendly.

Your helpful assistant lives on your Mac and keeps what matters close.

Private on your MacWorks offlineYours to shape
Page ready — select anything to edit itSelect an element to start editing
82%
After the build, these edits need no inference.

Website Studio changes the working page directly, keeps undo history, previews responsive sizes and saves the result back to the real HTML file.

Preview Responsive page and app testing Editor Files, symbols and diagnostics Agents Specialist activity and routing Calibration Match models to this Mac

Agentic creation studios

Direct a film. Build a song.
Keep the studio on your Mac.

Give Kynd the creative intent, then work with the plan—not a black box. Review shots before rendering, reshoot one take, reshape a chorus, generate an isolated instrument or repaint a few seconds without throwing the project away.

The Last Signal
ChatBuild
PreviewWebDesignerEditorStudioMusicAll tabs · 13
4 shots · 16.0s · 4 rendered
Generative motion ready · 720p · 1280×704
cinematic 35mm, deep forest green, slate blue and warm amber, low natural light
Motion & cut pendingThe look is set; render motion and assemble the cut.
Storyboard
Forest cabin at blue hour with the designer working inside1still+ Chat

Wide establishing shot of a timber cabin in a wet forest at blue hour

Slow push in · 4.0s Will use LTX
Close-up of the cabin router as its status light fades2motion+ Chat

Close-up of the router as its final status light fades to black

Crash zoom · 3.0s LTX take
Over-shoulder view of the local assistant continuing to respond3motion+ Chat

Over-shoulder view of the local assistant still responding

Track right · 5.0s LTX take
The designer lit by the warm workstation screen4still+ Chat

Warm screen light across the designer’s quiet reaction

Breathing still · 4.0s Will use LTX
Timeline16.0s · drag the right edge of a block to retime
1 · 4.0s2 · 3.0s3 · 5.0s4 · 4.0s
Shot 2
LTX takeThis shot already has an active generative motion take.
Asking the local model
Signal at Dawn
ChatBuild
PreviewWebDesignerEditorStudioMusicAll tabs · 13
Signal at DawnACE-Step ready · standard
4 clips · 0:48
Make with ACE-StepChoose a workflow
JJamYour inspiring bandmate · shape the idea, then build it in layersoriginal, produced, layered, dynamic
Full SongInstrumentalVocal

Let’s build this idea into a full arrangement. Start with a strong foundation, then use the Lego / Stem mode to add isolated parts without flattening the mix.

0:18.4 / 0:48− ━━━━━ +
4 layersDrag clips between layers
IntroVerseLiftOutro0:00    0:12    0:24    0:36    0:48
MasterMusic bedM  S
First take0:48
DrumsDrumsM  S
Live kit layer0:36 · lego
Analog bassBassM  S
Warm bass0:28 · extract
Synth liftSynthM  S
Final lift · take 20:16 · repaint
Starting the Music collaborator
01Plan before spending time

Chat turns a film idea into an editable shot plan. Rendering waits for explicit approval.

02Reshoot the exact take

Reference a shot in Chat, revise it, compare variants and cut only the active takes.

03Compose with a collaborator

Jam develops a brief into structure, tempo, key, tags and editable lyrics or instrumental direction.

04Build music in layers

Create full songs, isolated stems and repainted ranges, then arrange and export the mix.

Agent intelligence

A smaller model should get
a smarter system around it.

Kynd Code reduces ambiguity before asking the model to reason. That means fewer choices, better context and verification built into the loop.

01 · Focus

Ten tools before a hundred.

Focused Build starts with the essential read, write, edit, search, shell and task tools. It discovers specialised capabilities only when the job calls for them.

read_fileedit_filesearch_filesbashfind_tools+ task extras
02 · Route

The right specialist, not a bigger prompt.

Explorer, context gatherer, implementer, debugger and tester are different working modes for the same local model.

YouRouterImplementation
03 · Verify

Edits with a blast-radius check.

Language-server definitions, references and diagnostics help the agent understand what a write can affect—and whether it left the project healthy.

ModelPicker.tsx0 errors

Definition resolved

References checked

Diagnostics clean

04 · Learn

Fix it once. Reuse it locally.

Kynd records useful bad→good code patterns and can apply a known repair without spending another inference turn.

errorlocal patternfixed

Kynd inference

The server is part
of the product.

A local model should not have to pay the same prompt and memory costs on every turn. Kynd’s OpenAI-compatible inference layer is tuned around Apple Silicon, real model profiles and long coding sessions.

Conversation forksup to 37×

faster repeated prefill in the 20K-character cache microbenchmark.

11.2s → 0.3s
System prefix cache13× warm

when the exact tools and instructions are already cached.

5.1s → 0.4s
Compact tool schemas−55%

schema tokens in the measured 18-tool compact-mode example.

3,418 → 1,535
MoE prefill tuning492 tok/s

at the measured 2,048-token prefill step on Qwen3.6 35B A3B.

403 → 492 tok/s

Internal Kynd measurements on the cited Qwen3.6 35B A3B MLX setup. Hardware, model, quantisation and context change results; these are not cross-product benchmarks.

MODEL-AWARE INPUTSMac memory tierArchitecture + quantContext pressureTask + tool surface
Kynd RuntimeOpenAI-compatible · local only
fork cacheprefix cachedynamic KVMetal guard
ADAPTIVE ROUTESMLX / mlx_lmGGUF / llama.cppMTP-capable profilesVision hot-swap

Fits your Mac

Not the biggest model.
The best working fit.

Kynd detects model families and uses RAM-aware profiles for context, sampling and runtime behaviour. Benchmark Match can compare the models already on your machine with fixed local tests.

16 GB MacFocused Build
O

Ornith 1.0 9B

Agentic coding post-training with a practical OptiQ 4-bit footprint.

  • ~7.5 GB weights
  • Up to 32K calibrated context
  • Focused tool mode by default
64 GB MacHigh fidelity
Q

Qwen3.6 35B A3B

The higher-fidelity 8-bit profile with room for a larger working context.

  • ~35 GB 8-bit weights
  • Up to 131K calibrated context
  • Vision-capable profile
Also in the runtime: GGUF routing through bundled llama.cpp profiles, MTP-aware routes where supported, adaptive KV sizing, calibrated context ceilings and safe fallback paths.Explore the inference layer →

Private by design

Your unfinished ideas
stay unfinished on your Mac.

01Source stays localYour files are read and changed on the machine you own.

02Inference stays localThe primary coding model runs in unified memory—not behind an API account.

03Network tools are visibleSearch, browser and GitHub actions appear as explicit tools when you choose to use them.

Questions

Before you let a local agent
into the codebase.

Is Kynd Code a separate app from Kynd Agent?

Kynd Code is the coding and Build experience inside the Kynd desktop app. This site focuses on that local developer workflow; the download includes Chat and Build together.

Does it work without the internet?

Core model inference, file operations, editing, shell tools, memory and language-server checks can run locally. Features that inherently contact an external service—web search, GitHub or downloading a model—still need a connection and appear as visible tools.

Which models does it support?

Kynd has tuned profiles for current Qwen-family and Ornith MLX models, plus GGUF routes through llama.cpp and MTP-aware profiles where supported. The on-device benchmark and calibration screens help you judge what actually works on your Mac.

Is it really faster than a generic local setup?

Kynd’s own cache, schema and prefill benchmarks show large reductions in repeated local inference work. We do not present those as a benchmark against OpenCode, Cline or every possible provider configuration. The advantage we can substantiate is architectural: Kynd controls and tunes both the agent loop and its local inference layer.

What happens after the trial?

Every coding, Workbench and creation feature is open for the first 30 days without a card. Kynd’s assistant core remains useful for free; continued Build access is available through the existing one-off licence.

Build privately

Give your local model
a system built for it.

All Build and Workbench features are open for 30 days. No account, API key or card required.

macOS 14+ · Apple Silicon · 16 GB unified memory or more