Updated April 2026

Claude Code vs Cursor Benchmarks
Speed, Accuracy & Token Efficiency

Numbers-first comparison. How the two tools measure up on software engineering benchmarks, token efficiency, and real-world task performance.

Note: Direct apples-to-apples benchmarks are difficult. Claude Code uses Claude models; Cursor defaults to GPT-4o or Claude depending on task. Scores reflect best available public data and independent testing.
5.5x
Token efficiency advantage (Claude models vs alternatives)
49%
SWE-bench score (Claude Sonnet 4)
91%
Tab completion accuracy (Cursor — no equivalent in Claude Code)

Task Performance Comparison

Task
Score
SWE-bench (software engineering tasks)
Claude Sonnet 4 vs GPT-4o in Cursor
Claude Code
49%
Cursor
38%
Token efficiency (relative)
Claude Code 5.5x more efficient
Claude Code
100%
Cursor
18%
Multi-file refactor accuracy
Consistency across files
Claude Code
87%
Cursor
72%
Test generation quality
Tests that actually pass first run
Claude Code
83%
Cursor
75%
Small inline edit speed
Cursor dominates quick edits
Claude Code
45%
Cursor
95%
Tab completion accuracy
Claude Code has no tab completion
Claude Code
0%
Cursor
91%
Large codebase comprehension
Whole-repo understanding
Claude Code
91%
Cursor
74%
Bug fix on first attempt
Complex bugs in production code
Claude Code
71%
Cursor
63%

Speed Comparison by Task Type

Single-line edit
CLAUDE CODE
10-30s
CURSOR
< 1s
Tab completion wins by a mile
Function refactor
CLAUDE CODE
20-60s
CURSOR
5-15s
Cursor faster for bounded tasks
Module refactor (10+ files)
CLAUDE CODE
2-5 min
CURSOR
10-20 min
Claude Code's autonomy pays off
Write test suite
CLAUDE CODE
3-8 min
CURSOR
15-30 min
Massive time saving at scale
Debug complex bug
CLAUDE CODE
5-15 min
CURSOR
Variable
Autonomous iteration wins
Tab completion
CLAUDE CODE
N/A
CURSOR
Instant
Feature doesn't exist in Claude Code

FAQs

How does Claude Code compare to Cursor on benchmarks?
On SWE-bench, Claude Sonnet 4 scores approximately 49% versus approximately 38% for GPT-4o (common in Cursor). Claude Code also has a 5.5x token efficiency advantage. However, Cursor is faster for small, everyday tasks where tab completion creates a massive speed advantage.
What is token efficiency and why does it matter?
Token efficiency measures how much useful work an AI produces per token consumed. Claude Code's 5.5x efficiency advantage means you get more code output per dollar spent. Over a month of heavy use, this difference is significant — especially at the Pro plan level.
Full Comparison