Amp vs Claude Code: Model-Agnostic Orchestration vs Native Intelligence

Amp lets you use Claude, GPT-5.3, and Gemini 3 through one agent. Claude Code only runs Claude but optimizes every layer for it. We tested both on real projects.

March 4, 2026 · 1 min read

Summary

Quick Decision Matrix (March 2026)

  • Choose Amp if: You want to use the best model per task (Claude for coding, GPT-5.3 for reasoning, Gemini for review), need team thread sharing, or prefer IDE-agnostic tooling
  • Choose Claude Code if: You need coordinated Agent Teams with shared task lists and dependency tracking, deterministic outputs, or deep CLAUDE.md-driven workflows
  • Choose both if: Your team already uses Claude Code for orchestration and wants Amp for tasks that benefit from GPT-5.3 deep reasoning
800K+
Developers on Sourcegraph platform (Amp's parent)
135K/day
Claude Code GitHub commits (~4% of all public)
$10/day
Amp free tier daily grant
200K
Amp context window (tokens)

The core trade-off: Amp gives you access to every frontier model through one interface, with team collaboration built in. Claude Code gives you one model family with the deepest possible integration, including Agent Teams that coordinate multiple sub-agents with shared task lists. Amp is the better team tool. Claude Code is the better orchestration engine.

Stat Comparison

These tools optimize for different things. Amp maximizes model coverage and team features. Claude Code maximizes agent depth and consistency.

Amp (Sourcegraph)

Model-agnostic orchestrator with team threads

Model Flexibility
Team Collaboration
Agent Specialization
IDE Coverage
Deep Reasoning
Best For
Multi-model routingTeam knowledge sharingDeep reasoning tasksIDE flexibility

"Best model diversity and team features in any terminal agent."

🎯

Claude Code

Native Claude agent with coordinated teams

Model Flexibility
Team Collaboration
Agent Specialization
IDE Coverage
Deep Reasoning
Best For
Multi-agent orchestrationComplex refactoringDeterministic outputsCLAUDE.md workflows

"Deepest agent coordination, but locked to one model provider."

Platform Stats (March 2026)

Amp

  • Sourcegraph: 800K+ developers, 54B+ lines indexed
  • Models: Claude Opus 4.6, GPT-5.3-Codex, Gemini 3 Pro
  • CLI + VS Code + JetBrains + Neovim + Zed + Cursor
  • Spun off into Amp Inc. (Quinn Slack, Beyang Liu)
  • Enterprise: $59/user/month with SSO

Claude Code

  • 71,500 GitHub stars, 51 contributors
  • Ships multiple releases per day
  • VS Code: 5.2M installs, 4.0/5 rating
  • Agent Teams (research preview), hooks, auto-memory
  • ~135K GitHub commits/day (~4% of all public commits)
Model diversity
Amp
Claude
Multi-agent coordination
Amp
Claude
Team knowledge sharing
Amp
Claude
Deterministic outputs
Amp
Claude

Model Routing: Amp's Core Advantage

Amp does not just support multiple models. It routes to different models for different subtasks within the same session. This is architecturally different from tools that let you switch models manually.

TaskAmp ModelClaude Code Model
Primary codingClaude Opus 4.6 (Smart mode)Claude Opus 4.6 or Sonnet 4.6
Deep reasoningGPT-5.3-Codex (Deep mode)Claude Opus 4.6 extended thinking
Code reviewGemini 3 (Review agent)Claude (same model)
Image generationGemini 3 Pro (Painter)Not supported
Complex debuggingGPT-5.2 (Oracle, auto-triggered)Claude with extended thinking
Cross-repo searchLibrarian (Sourcegraph backend)Grep + Glob tools

Three Modes, Three Models

Amp has three primary modes. Smart uses Claude Opus 4.6 for standard coding tasks. Rush uses a faster, cheaper model for small, well-defined changes. Deep engages GPT-5.3-Codex for extended reasoning on hard problems. You can switch modes mid-session with Ctrl+S or let Amp auto-route.

The Oracle is separate from modes. It uses GPT-5.2 with medium reasoning and can be triggered automatically when Amp detects a task is unusually complex, or manually by saying "use the oracle." This means a single Amp session might use Claude for the initial implementation, auto-escalate to the Oracle for a tricky debugging step, and finish with Gemini for a code review.

Claude Code: One Model, Full Stack

Claude Code only runs Claude models. The trade-off is that every layer of the agent is tuned specifically for Claude: the prompting strategy, tool use patterns, context management, and error recovery are all co-designed with the model. When Claude Code spawns Agent Teams, every sub-agent is Claude. This consistency makes multi-agent coordination more predictable. In an Amp subagent workflow, different models might produce incompatible output styles that the orchestrator has to reconcile.

The Model Lock-in Question

If Anthropic ships a bad Claude update, Claude Code users have no fallback. Amp users can switch to GPT-5.3 or Gemini within minutes. This has already happened: when Claude Sonnet 4.5 initially shipped with regressions in tool use, Amp users switched to GPT-5 while Claude Code users waited for a fix.

Subagent Architecture

Both tools support subagents, but the implementations are very different. Amp has specialized, purpose-built agents. Claude Code has general-purpose agents that coordinate through a shared task system.

AspectAmpClaude Code
Subagent modelSpecialized: Oracle, Librarian, Painter, ReviewGeneral-purpose Agent Teams
CoordinationIndependent, no inter-agent messagingShared task list, dependency tracking, messaging
Context isolationEach subagent has isolated contextEach agent in worktree, shared team config
Max agentsUser-specified (e.g., 'use 3 subagents')Team-lead spawns as needed
Cross-repo searchLibrarian: GitHub + Bitbucket EnterpriseFile-level grep within project
Visual generationPainter: Gemini 3 Pro imagesNot available

Amp: Specialist Agents

Each Amp subagent is purpose-built. The Oracle reasons through complex problems with GPT-5.2. The Librarian searches across repositories using Sourcegraph's code intelligence. The Painter generates images with Gemini 3. You invoke them explicitly or Amp routes to them automatically.

Claude Code: Coordinated Teams

Claude Code's Agent Teams are general-purpose. Each agent gets its own context window and git worktree. They share a task list with dependency tracking and can send messages to each other. The team-lead agent coordinates, blocking downstream tasks until dependencies complete.

Amp: Subagent Workflow

# Use subagents explicitly
$ amp "Convert all CSS files to Tailwind. Use 3 subagents."
# Amp spawns 3 isolated agents, each handling a subset of files

# Oracle auto-triggers on complex debugging
$ amp "Debug this race condition in the payment flow"
# Amp detects complexity, escalates to Oracle (GPT-5.2)
# Oracle reasons through the concurrency issue
# Primary agent applies the fix

# Code review with Gemini
$ amp "Review the PR for security issues"
# Review agent uses Gemini 3 for analysis

Claude Code: Agent Teams Workflow

# Agent Teams with dependency tracking
$ claude "Build the payment integration"

# Claude Code automatically:
# 1. Creates team with shared task list
# 2. Spawns researcher agent -> explores Stripe SDK
# 3. Spawns implementer agent -> blocked until research done
# 4. Spawns test agent -> writes tests in parallel
# Agents message each other: "research complete, 3 patterns found"
# Task deps prevent implementer from starting early

Amp's approach is more modular. You pick which specialist agent to use, or let Amp decide. Claude Code's approach is more integrated. The team-lead agent orchestrates everything, tracking dependencies and passing context between agents. For tasks where subtasks are independent (CSS-to-Tailwind conversion, batch file processing), Amp's approach is simpler. For tasks with complex dependencies (full-stack features, multi-service refactors), Claude Code's coordination wins.

Team Features: The Biggest Gap

This is where the tools diverge most sharply. Amp was built for dev teams from the start. Claude Code was built for individual developers and is adding team features incrementally.

FeatureAmpClaude Code
Thread sharingPublic, unlisted, workspace, group-sharedNot available (agent-to-agent only)
Knowledge reuseSearch past threads by keyword, file, authorCLAUDE.md + auto-memory per project
Public profilesampcode.com/@usernameNot available
Enterprise SSOOkta, SAML, directory syncThrough Anthropic org management
Cost attributionPer-group credit trackingPer-user via Anthropic dashboard
Command allowlistingDefine exactly which CLI commands agents can runPermission prompts per command
AnalyticsEnterprise analytics APIBasic usage stats

Thread Sharing Changes the Workflow

When a developer solves a hard problem with Amp, they can share that thread with the team. Other developers can search it by keyword, file path, or date. They can reference it in their own threads via @-mention. This creates an organic knowledge base of solved problems, searchable by anyone on the team.

Claude Code does not have an equivalent. Its knowledge sharing is through CLAUDE.md files (static instructions) and auto-memory (per-project context that persists across sessions). These work well for individual developers but do not capture the interactive problem-solving process that threads preserve.

Enterprise Security

Amp offers zero data retention for enterprise customers, meaning text inputs are not stored by the LLM providers. It also has MCP server approval workflows (untrusted repositories cannot auto-execute code), IP allowlisting, and managed settings that admins push to all users.

Claude Code's security model relies on permission prompts (approve/deny per command), auto-accept mode for trusted workflows, and hooks for custom automation. It lacks the centralized admin controls that Amp provides for larger organizations.

Pricing: Pay-Per-Token vs Subscription

Completely different pricing models. Amp charges for what you use. Claude Code bundles into subscriptions.

TierAmpClaude Code
Free$10/day grant (closed to new signups)No free tier
IndividualPay-as-you-go, no markup on model costsPro: $20/mo (usage limits apply)
Mid-tierSame pay-as-you-goMax 5x: $100/mo (5x Pro usage)
Power userSame pay-as-you-go (scales with usage)Max 20x: $200/mo (20x Pro usage)
Enterprise$59/user/mo + 50% premium on creditsCustom pricing via Anthropic

Which Is Cheaper?

It depends on usage volume. Amp's free tier ($10/day, ~$300/month value) is extremely generous for users who got in. For paid users, Amp passes through model costs at par, so you pay exactly what Claude, GPT-5.3, and Gemini charge. If you spend under $100/month on model costs, Amp is cheaper than Claude Max 5x. If you consistently use $200+/month in model costs, Claude Max 20x gives you unlimited usage at a fixed price, which is cheaper.

The key difference: Claude Code's subscription means you pay the same whether you use it lightly or heavily. Amp's pay-as-you-go means light months are cheap but heavy months can exceed subscription costs. For teams, Amp's pooled workspace credits add flexibility that per-seat subscriptions lack.

The Agent Teams Cost Multiplier

Claude Code's Agent Teams multiply limit consumption proportionally to the number of sub-agents spawned. Three agents working in parallel consume limits 3x faster. On the $20 Pro tier, this means you might exhaust your allocation in a single complex task. On Amp, subagent costs are transparent: you see the exact token cost per agent in real time.

CLI and Editor Support

Both are terminal-first tools, but Amp has broader editor coverage.

PlatformAmpClaude Code
Terminal CLIYes (custom high-performance TUI)Yes (Node.js-based)
VS CodeExtensionExtension (5.2M installs)
JetBrainsExtension (IntelliJ, WebStorm, GoLand)Extension
NeovimDedicated pluginCommunity plugins
ZedSupportedNot supported
CursorSupported (runs inside Cursor)Not supported (competitor)
WindsurfSupportedNot supported

Amp runs inside Cursor and Windsurf as an extension, which is a notable competitive move. You can use Amp's model routing and team features inside a competitor's editor. Claude Code, as an Anthropic product, does not integrate with competing AI editors.

CLI Differences

Amp's CLI uses a custom TUI framework that the team says eliminates the flickering common in terminal-based agent interfaces. It supports 7 built-in themes, custom themes via colors.toml, and keybindings configurable per OS and IDE. Claude Code's CLI is Node.js-based, ships multiple times per day, and prioritizes features (hooks, Agent Teams, auto-memory) over UI polish.

AGENTS.md vs CLAUDE.md

Both tools support project-level instruction files. Claude Code uses CLAUDE.md. Amp uses AGENTS.md (with YAML frontmatter support for glob-scoped instructions). Amp maintains backward compatibility with CLAUDE.md files, so switching from Claude Code to Amp requires only renaming the file. Both formats let you encode architecture decisions, coding conventions, and build/test commands that the agent follows.

Failure Modes

An independent reviewer deployed both tools on the same task: building and deploying a todo app to Fly.io. The results reveal how each tool fails differently.

Amp Failure Patterns

  • Overproduction: Added linting, testing, and memory allocation beyond stated requirements
  • Silent continuation: When local Docker testing failed, Amp continued without pausing for user input
  • Model transition costs: When the Oracle escalates from Claude to GPT-5.2, the reasoning style shift can produce inconsistent code conventions within a single task

Claude Code Failure Patterns

  • Assumption-making: Chose in-memory storage without asking (Amp asked which database approach to use)
  • Missing infrastructure: Did not set up persistent volumes for the deployment (Amp did)
  • Health check bugs: The health check implementation contained a bug that prevented proper operation (Amp's worked)
  • CSS embedding: Put CSS directly in HTML instead of separate files

The Proactivity Difference

In the Fly.io deployment test, Amp proactively asked whether the user wanted in-memory or persistent SQLite storage, then set up a Fly volume accordingly. Claude Code defaulted to in-memory without asking. This illustrates a broader pattern: Amp asks more questions upfront. Claude Code makes more assumptions. Which you prefer depends on whether you want fewer interruptions or fewer surprises.

Both tools successfully completed the full task, producing functional deployed applications. The failures were in quality decisions and infrastructure setup, not in task completion itself.

Where Amp Wins

Multi-Model Tasks

When a task benefits from different models at different stages: Claude for implementation, GPT-5.3 for deep reasoning, Gemini for visual review. Amp handles this routing automatically.

Team Knowledge Sharing

Shared threads, searchable by keyword and file path, create an organic knowledge base of solved problems. Public profiles at ampcode.com/@username let teams showcase solutions.

Editor Flexibility

Works in VS Code, JetBrains, Neovim, Zed, Cursor, and Windsurf. If your team uses different editors, Amp normalizes the agent experience across all of them.

Model Resilience

When one model provider has an outage or ships a regression, Amp users switch modes and keep working. Claude Code users wait. This resilience is underrated until you need it.

Best For: Teams That Value Flexibility

If your team uses multiple editors, wants to avoid model lock-in, and values shared knowledge from past agent sessions, Amp is the better choice. The Sourcegraph heritage gives it strong code intelligence foundations for cross-repository work. The free tier ($10/day grant) also makes it accessible for evaluation without commitment.

Where Claude Code Wins

Coordinated Multi-Agent Tasks

Agent Teams with dependency tracking, inter-agent messaging, and shared task lists are unmatched. 16 Claude agents built a 100K-line C compiler in Rust that compiles the Linux kernel 6.9 for ~$20K in API cost.

Deterministic Instruction Following

Claude Code follows plans more reliably than Amp. When you need the agent to stick to a spec without improvising, Claude's deterministic outputs and CLAUDE.md system are stronger.

Context Window

Claude Opus 4.6 has a 1M token context window (beta). Amp's context caps at 200K tokens. For massive codebases and long sessions, Claude holds more in memory.

Benchmark Performance

Claude Opus 4.6 leads SWE-bench Verified at 80.8% and scores 55.4% on SWE-bench Pro. Terminal-Bench 2.0 shows Claude Code at 58.0%. These benchmarks measure coding ability, not agent features, but they matter for output quality.

Best For: Complex Orchestration

If your work involves splitting large tasks across multiple coordinated agents that need to share context and track dependencies, Claude Code's Agent Teams are the best implementation available. The 1M token context window, hooks system for automation, and auto-memory for cross-session learning compound into a deeper single-developer experience than Amp offers.

"Amp is really the one agent where I don't hesitate to say it is consistently better." (Developer review, comparing to other agents excluding Claude Code)

Decision Framework

Your SituationBest ChoiceWhy
Team with mixed editorsAmpWorks in VS Code, JetBrains, Neovim, Zed, Cursor
Complex multi-agent refactoringClaude CodeAgent Teams with task deps + inter-agent messaging
Model vendor diversificationAmpRoutes to Claude, GPT-5.3, Gemini per task
Predictable monthly costClaude Code$20-200/mo fixed subscription
Team knowledge sharingAmpThread sharing, search, public profiles
Massive codebase (1M+ tokens)Claude Code1M token context vs Amp's 200K
Cross-repo code searchAmpLibrarian agent + Sourcegraph backend
Deterministic plan followingClaude CodeStronger instruction adherence
Enterprise admin controlsAmpSSO, command allowlisting, analytics API
Deep reasoning on hard problemsAmpGPT-5.3-Codex deep mode + Oracle

Frequently Asked Questions

Is Amp or Claude Code better for coding in 2026?

They optimize for different things. Amp gives you access to Claude, GPT-5.3, and Gemini through one agent with team collaboration features. Claude Code gives you Claude-only with the deepest agent coordination available (Agent Teams with dependency tracking and inter-agent messaging). For team-oriented workflows with model flexibility, Amp wins. For solo developer orchestration of complex multi-agent tasks, Claude Code wins.

Can Amp use Claude models?

Yes. Amp's Smart mode uses Claude Opus 4.6 as the default model. It switches to GPT-5.3-Codex for Deep mode (extended reasoning), GPT-5.2 for the Oracle (complex debugging), and Gemini 3 Pro for the Painter (image generation) and code review. You get Claude's coding ability plus access to other models' strengths.

How much does Amp cost compared to Claude Code?

Amp offers a free tier ($10/day grant, closed to new signups) and pay-as-you-go pricing with no markup on model costs. Enterprise is $59/user/month. Claude Code requires a Claude subscription: Pro ($20/mo), Max 5x ($100/mo), or Max 20x ($200/mo). Light users pay less with Amp. Heavy users often pay less with Claude Max subscriptions.

Does Amp have CLAUDE.md support?

Amp uses AGENTS.md (with YAML frontmatter for glob-scoped instructions) but maintains backward compatibility with CLAUDE.md files. Switching requires renaming the file. Both formats encode project instructions that the agent follows.

Which has better subagent support?

Different approaches. Amp has specialized agents (Oracle, Librarian, Painter, Review) with isolated context. Claude Code has general-purpose Agent Teams with shared task lists, dependency tracking, and inter-agent messaging. Amp's agents are more diverse. Claude Code's agents are better coordinated. For independent parallel tasks, Amp's approach is simpler. For dependent multi-step workflows, Claude Code's coordination is stronger.

Morph's Fast Apply Works with Both Amp and Claude Code

Morph's fast apply model improves edit quality in any coding agent. Use it as an MCP server or API endpoint. Works with Amp, Claude Code, Cursor, Codex, and any tool that supports MCP.

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