SWE-2 vs Willow on IOS: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of SWE-2 and Willow on IOS — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

SWE-2

Cognition

Paid

Cognition's coding model that scores 50.0% on FrontierCode 1.1 Main at 64% lower cost than comparable frontier models.

Pareto-Frontier Cost Efficiency: Matches GPT-5.6 Sol and Fable 5/5.1 on coding benchmarks at a fraction of their price and comes within a few points of GPT-6 Astra at roughly a quarter of the cost.
Single-Run Multi-Effort RL: A reinforcement learning algorithm trains all reasoning-effort levels in one run, applying a per-level linear cost penalty derived from the base model's local frontier slope.
Focused Codebase Exploration: Stronger engineering judgment lets the model decide which parts of a repository matter, cutting mean steps per run from 127 to 53 at medium effort.
Selectable Effort Levels: Ships medium, high and max reasoning settings so teams can trade additional steps and cost for accuracy on harder tasks.
End-to-End Test Writing: Produces tests that validate an implementation end to end, catching regressions and edge cases more reliably than previous SWE models.
Resourceful Task Recovery: When an expected route is blocked — an unavailable MCP integration, for example — it finds an alternative path to the same answer within the user's stated boundaries.
Efficient Training and Serving Stack: NVFP4/FP8 kernels, quantization-aware training and an online draft model cut memory use and train-inference mismatch despite nearly 3x the base parameters of SWE-1.7.
Hardened Verifier Flywheel: Triples the number of RL environments, adds instruction-following overlays, and uses earlier SWE-2 checkpoints to iteratively strengthen verifiers.

Agentic Software Engineering: Powering Devin sessions that plan, edit, build and test changes across a real repository with minimal supervision.
Cost-Sensitive Coding at Scale: Teams running large volumes of automated coding tasks pick a model that holds frontier-adjacent accuracy at a materially lower per-task cost.
Terminal and Tooling Workflows: Strong Terminal-Bench results suit tasks driven through shell commands, build systems and command-line tooling.
Regression Test Generation: Generating end-to-end tests for existing implementations to catch edge cases before a release.
Effort-Tiered Task Routing: Routing simple tickets to medium effort and hard migrations to high or max effort within the same model deployment.
Benchmark and Model Evaluation: Engineering leaders compare coding model options on published FrontierCode, DeepSWE and Terminal-Bench numbers alongside cost.

Willow Voice

Freemium

Fast, context-aware speech-to-text dictation for Mac and iPhone with custom dictionaries and privacy-focused handling.

Real-time Dictation: Converts spoken input into text on macOS and iPhone with immediate transcription for emails, documents, notes, and messages to speed up writing workflows.
Context-Aware Processing: Uses contextual language understanding to improve accuracy and punctuation, adapting transcription to sentence structure and conversational context.
Custom Dictionaries: Allows users to add domain-specific vocabulary, names, and technical terms so transcriptions reflect industry- or user-specific language correctly.
Automatic Editing & Formatting: Applies automatic edits, punctuation, and formatting rules to raw transcribed text to reduce manual cleanup after dictation.
App Integrations: Designed to work across common workflows and apps (email, documents, note-taking, messaging, and the Cursor editor) to insert transcribed text where users work.
Privacy-Focused Handling: Emphasizes secure and private handling of voice data and transcription results to protect user information and sensitive content.
Real-time speech-to-text dictation on iPhone and Mac
Context-aware automatic edits to improve transcript quality
Custom dictionaries and terminology support
Privacy-focused operation with options for local/self-hosted inference
Integration-ready: supports use in email, documents, note-taking, messaging, and developer workflows
Willow Inference Server for self-hosted STT, TTS, LLM, and WebRTC inference

Writing emails hands-free: Dictate long or short emails on Mac or iPhone to compose messages faster without switching to a keyboard.
Meeting and lecture notes: Capture spoken content during meetings or lectures and get edited, punctuated notes ready for review and sharing.
Document drafting and editing: Rapidly create drafts of reports, articles, or documents via voice, with automatic formatting reducing post-edit effort.
Messaging and quick replies: Compose rapid, accurate message responses in chat and SMS apps using voice input on iPhone.
Technical and domain-specific transcription: Use custom dictionaries to accurately transcribe industry jargon, code-related terms, names, and acronyms for developer or specialist workflows (e.g., Cursor integration).
Accessibility and hands-free computing: Provide an accessible input method for users with mobility or dexterity impairments who need reliable speech-to-text on macOS and iOS.
Hands-free email and document composition on iPhone and Mac
Faster note-taking and meeting transcription
Voice-driven messaging and chat input
Accessibility for users needing speech input
Enterprise/local deployment using Willow Inference Server for private on-premise transcription and TTS
Developer integration for embedding STT/TTS/LLM capabilities into apps or real-time WebRTC flows