Evidence-based comparison across real engineering benchmarks, SWE tasks, SIMD optimization, and enterprise procurement criteria.
Daniel Liezrowice · ESL · Based on controlled benchmarks & community evidence
Update — July 2026: Original comparison published April 15, 2026. Model and feature inventory is historical. Newer same-model benchmarks (Claude Fable 5 held constant) show Amp 2.1× faster and 2.6× cheaper — see Baboons Benchmark · Final Scores. Amp modes renamed: Smart/Rush/Deep → Low/Medium/High/Ultra.
Add allocationTraceID to DRA lifecycle across 27,579 files. Zero human intervention. Zero coaching.
| Metric | Ampcode | Claude Code | Winner |
|---|---|---|---|
| Engineering Score | 8.85 | 8.84 | ≈ Tie |
| Procurement Score | 9.08 | 8.45 | Ampcode ▲ |
| Cold-Start Time | 1.0–1.6 min | 64 min | Ampcode (40× faster) |
| Repeatability | 9.9/10 | 6.8/10 | Ampcode ▲ |
| Autonomy | 10/10 | 10/10 | Tie |
| Patch Size | 6 files (+31 lines) | 14 files (+80 lines) | Trade-off |
Source: github.com/zuwasi/Compare-Ampcode-Vs-Claudecode-on-a-real-Kubernetes-engineering-task · GPT-5.4 as independent judge
Management & Procurement Weighted Model (real-world decision criteria)
Ampcode wins the procurement-weighted model by +0.63 points
50 Python · 25 C++ · 25 CUDA — From easy to extreme (compilers, VMs, GCs, lock-free structures)
xhigh)Extreme: Compiler lexer, bytecode VM, GC, Raft consensus, type inference, CUDA dynamic parallelism
Source: github.com/zuwasi/QuickSWE · Live Dashboard ↗
Responding to Daniel Lemire's challenge — who generates the fastest low-level code?
| Implementation | ns/string | Speedup |
|---|---|---|
Classic C++ (std::count -O3) | 67.05 | 1.00× |
| SSE2 intrinsics | 39.26 | 1.71× |
| AVX2 intrinsics | 33.97 | 1.97× |
| AVX2 4-accumulator | 30.91 | 2.17× |
🔑 Ampcode out-optimized GCC 15.2's own SIMD vectorizer — the baseline was already using AVX2!
| Feature | Claude/Grok | Ampcode |
|---|---|---|
| Architecture | ARM64/NEON | x86-64/AVX2 |
| Baseline | Scalar loop | Already SIMD |
| Best Speedup | ~8× (scalar→SIMD) | 2.17× (SIMD→SIMD) |
| AI Efficiency | Multiple rounds | Single session |
| Max Unrolling | 4-acc (64B) | 8-acc (128B) |
Lemire beat a scalar baseline (easy win). Ampcode beat the compiler's own optimizer — a much harder challenge.
Source: Ampcode Assembly Benchmark Thread · Platform: Intel Core Ultra 9 275HX (Arrow Lake)
Reproducing Yoav Abrahami's methodology (Wix Engineering). Same task, same criteria — Ampcode replaces Cursor.
| Criterion | Claude Code | Cursor |
|---|---|---|
| Initial Planning | 4/5 | 5/5 |
| Edge Case Handling | 4/5 | 5/5 |
| Debugging & Iteration | 3/5 | 5/5 |
| Testing Discipline | 3/5 | 5/5 |
| Architectural Awareness | 2/5 | 5/5 |
| Out-of-Scope Gaps | 2/5 | 5/5 |
| TOTAL | 18/30 | 30/30 |
Claude Code scored poorly against Cursor.
Ampcode has the architectural advantages that made Cursor beat Claude Code: multi-model routing, sub-agents, and IDE-native intelligence — but in a CLI-first agent designed for enterprise teams.
Source: Counterpoint Study Repo
Analysis of Winder.ai's Claude Code field report — how Amp solves each pain point.
| Problem (Claude Code) | Amp Solution | Why Amp Wins |
|---|---|---|
| Phantom features — dead code rebuilt | Call-graph pre-filter analysis | Auto-skips dead symbols before migration |
| Context window blowup — missed endpoints | Parallel Task sub-agents | One agent per endpoint, isolated context |
Architectural drift — everything in internal/ |
Scoped AGENTS.md per directory | Enforces layout & import rules upfront |
| Dead code accumulation | Automated sweeps after every task | Not manual "ask AI to check" |
| No integration tests during migration | tmux smoke tests at phase boundaries | Spins up app, hits APIs, compares outputs |
| Stateless resumption (reads file each session) | Ralph skill with dependency tracking | State-aware task progression |
Consistent 1.0–1.6 min across 3 cold starts
Single cold start on same K8s task
Claude Code is locked to one model family. Ampcode picks the best model for every sub-task.
Primary code generation, editing, and reasoning
Deep reasoning, code review, architecture decisions, debugging complex bugs
Quick, well-defined tasks at lower cost and higher speed
Searches and reads all public + your private GitHub repos. Understands framework internals, library code, cross-repo dependencies — no copy-pasting documentation.
Image generation, custom skills (MISRA analysis, CVE lookup, Mathematica), MCP server integration, extensible toolbox system. Claude Code has none of this modularity.
Claude Code = Personal tool. Ampcode = Team infrastructure.
Recurring themes: Faster · Smarter model routing · Better sub-agents · Team collaboration · Superior CLI
| Dimension | Ampcode | Claude Code | Winner |
|---|---|---|---|
| K8s Procurement Score | 9.08 | 8.45 | ⚡ Ampcode |
| K8s Engineering Score | 8.85 | 8.84 | ≈ Tie |
| Repeatability (Cold Start) | 9.9/10 | 6.8/10 | ⚡ Ampcode |
| Cold-Start Speed | 1.3 min | 64 min | ⚡ Ampcode (40×) |
| SIMD Optimization | Beat compiler's SIMD | Beat scalar only | ⚡ Ampcode |
| Cross-Provider Models | Opus + GPT-5.4 + Gemini | Anthropic only | ⚡ Ampcode |
| Sub-Agent Architecture | Native + Oracle + Librarian | Explore/Plan/Custom | ⚡ Ampcode |
| Team Thread History | Searchable + Shareable | Session-level only | ⚡ Ampcode |
| Cross-Repo Intelligence | Librarian | None | ⚡ Ampcode |
| Single-Run Patch Breadth | 6 files | 14 files | 🟠 Claude |
Across all measured dimensions, Ampcode dominates.
Cold-start execution
True cold-start consistency
Best model for every task
Claude Code is a capable solo tool. Ampcode is the frontier coding agent for engineering teams — faster, more repeatable, multi-model intelligent, team-collaborative, and provably safer.
Daniel Liezrowice · ESL · April 2026 (updated July 2026)