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.

Start building free ↓ Watch the real workflow →

✓No API key ✓No account ✓30 days fully open ✓Your code stays local

Real Kynd Build interface

Explore → edit → verify → preview

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.↑

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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

Ornith 1.0 9BBest agentic fit for 16 GB unified memory

Selected

Qwen3.6 35B A3BNeeds 32 GB · 65K calibrated context

Details

Activity⌘ Agent›_ Shell⌄

Searching project symbols…

Your model→Kynd inference→Focused agent loop→Files + LSP→Live 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

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

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

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

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.

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

01
“Build me a landing page.”Agent finds files, writes code, renders.
wait
02
“Change that headline.”Agent finds the same component again.
wait
03
“Try a warmer green.”Another prompt, patch and render.
wait
04
“Add one line above the button.”Another model turn for a tiny edit.
wait

Kynd Code workflowBuild once, shape directly

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

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

body › main › section.hero

↑↓▣⌫

PRIVATE BY DESIGN

Local AI,
made friendly.

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

↯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.

Chat + Studio share one storyboard

The real staged flow is plan → approve → prepare stills → review the look → approve motion and the cut.

4 shots · 16.0s · 4 rendered

Generative motion ready · 720p · 1280×704 Quality Auto · 720p · 1280×704⌄ Motion Hero LTX · advanced + key shots⌄

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 inside

1still+ Chat

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

Close-up of the cabin router as its status light fades

2motion+ Chat

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

Over-shoulder view of the local assistant continuing to respond

3motion+ Chat

Over-shoulder view of the local assistant still responding

The designer lit by the warm workstation screen

4still+ Chat

Warm screen light across the designer’s quiet reaction

Timeline16.0s · drag the right edge of a block to retime

1 · 4.0s2 · 3.0s3 · 5.0s4 · 4.0s

Shot 2

What the lens sees

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

Image movement fast 2D fallback Video camera movement LTX Seconds

LTX takeThis shot already has an active generative motion take.

Action & scene motion optional LTX detail; the selected camera preset is applied first

The final green indicator falls dark while the cabin light and rain remain alive.

Narration spoken over this shot — leave empty for silence

JJam and Music Studio edit the same project session

Full Song, Lego / Stem and Repaint call the real ACE‑Step production tools; arranging and mixing stay available locally.

≋Signal at DawnACE-Step ready · standard

BPM 92Key E MinorTime 4/44 clips · 0:48

Make with ACE-StepChoose a workflow

JJamYour inspiring bandmate · shape the idea, then build it in layersoriginal, produced, layered, dynamic

What should we make?

A hopeful electronic score that starts intimate, then opens into warm analog synths and live-feeling drums.

Full SongInstrumentalVocal

Song structure Editable before generation

[Intro] [inst]
[Verse] [inst]
[Chorus] [inst]
[Outro] [inst]

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.

ACE caption

A hopeful electronic score that starts intimate, then opens into warm analog synths and live-feeling drums.

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.

You→Router→Implementation

◇

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.

error→local pattern→fixed

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

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

32 GB MacRecommended

Qwen3.6 35B A3B

A 35B mixture-of-experts model with roughly 3B active parameters per token.

~20 GB UD 4-bit weights
Up to 65K calibrated context
Fork + prefix cache enabled

64 GB MacHigh fidelity

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.

Download for Apple Silicon ↓See the workflow again ↑

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

Your local modelcan build more.

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

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

One prompt builds it.Then shape it instantly.

Local AI,made friendly.

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

A smaller model should geta smarter system around it.

Ten tools before a hundred.

The right specialist, not a bigger prompt.

Edits with a blast-radius check.

Fix it once. Reuse it locally.

The server is partof the product.

Not the biggest model.The best working fit.

Ornith 1.0 9B

Qwen3.6 35B A3B

Qwen3.6 35B A3B

Your unfinished ideasstay unfinished on your Mac.

Before you let a local agentinto the codebase.

Give your local modela system built for it.

Your local model
can build more.

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

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

One prompt builds it.
Then shape it instantly.

Local AI,
made friendly.

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

A smaller model should get
a smarter system around it.

The server is part
of the product.

Not the biggest model.
The best working fit.

Your unfinished ideas
stay unfinished on your Mac.

Before you let a local agent
into the codebase.

Give your local model
a system built for it.