QUICK VERDICT — JULY 2026
● Best benchmark accuracy: Claude Code — 80.4% SWE-bench Pro vs Grok Build's 64.7%
● Best per-task cost: Grok Build — $2.49 per completed task vs $11.80 for Claude Code (Artificial Analysis, July 2026)
● Best token efficiency: Grok Build — 15,954 output tokens per SWE task vs 67,020 for Claude Code (4.2x fewer tokens)
● Best context window: Grok Build — 500K tokens vs Claude Code's 200K
● Best for hard correctness-critical tasks: Claude Code — 80.4% vs 64.7% means 16 more tasks completed correctly per 100
Full Comparison Table
| Tool |
Model |
Input /1M |
Output /1M |
Context |
SWE-bench Pro |
Cost/task (AA) |
| Claude Code |
Fable 5 |
$10 |
$50 |
200K |
80.4% #1 |
$11.80 |
| Grok Build |
Grok 4.5 |
$2 |
$6 |
500K |
64.7% |
$2.49 |
Cost per task from Artificial Analysis standardised SWE-bench measurements, July 2026. Token counts: Grok 4.5 averages 15,954 output tokens per task vs Fable 5's 67,020 — 4.2x fewer, explaining the per-task cost gap despite higher per-token rates on Fable 5.
The Benchmark Gap — And Why It Is Not the Whole Story
Claude Code (Fable 5) leads SWE-bench Pro 80.4% to 64.7% — a 15.7 percentage point gap that translates to approximately 16 more correctly completed tasks per 100 agentic coding runs. For tasks where an incorrect output requires human intervention to identify, debug, and restart, those 16 additional correct completions represent real saved time. The SWE-bench Pro gap is the primary reason to choose Claude Code over Grok Build for hard, correctness-critical coding work.
The per-task cost gap runs in the opposite direction. Grok 4.5 uses an average of 15,954 output tokens to complete SWE-bench Pro tasks. Fable 5 uses 67,020 output tokens — 4.2x more. At Grok 4.5's $6/M output rate and Fable 5's $50/M output rate, the combined effect produces a $2.49 vs $11.80 per-task cost differential. At scale — 1,000 coding tasks per month — that is $2,490 vs $11,800. At 10,000 tasks per month it is $24,900 vs $118,000. For high-volume agentic coding pipelines where task failure rate is acceptable and human review catches errors, Grok Build's economics are dramatically better.
The Real Decision Framework
Choose Claude Code when: Task correctness directly affects production systems, incorrect outputs require expensive human debugging, your task volume is low (under 500/month), or you are working on hard reasoning problems where the 15.7% accuracy gap is meaningful.
Choose Grok Build when: Task volume is high (1,000+ per month), human review catches errors before production, you need more than 200K context (Grok Build provides 500K), or the 4.7x cost difference is material to your budget.
The hybrid approach: Use Grok Build for high-volume, lower-stakes tasks (test generation, boilerplate, documentation) and Claude Code for low-volume, high-stakes tasks (production refactors, security-critical code, architecture changes). This is the optimal cost-accuracy split given the current benchmark and pricing landscape.
Grok Build's Real Advantages Beyond Cost
Two structural advantages of Grok Build that the benchmark comparison does not capture: the 500K context window and the live X data integration. Claude Code's 200K context window means large codebases must be chunked or summarised before ingestion. Grok Build's 500K window can handle significantly larger repositories in a single pass — relevant for monorepo work or any codebase exceeding 100,000 lines of code. The live X firehose gives Grok Build awareness of current API changes, package updates, and breaking changes in real-time — something no other coding agent has. For tasks involving recently changed external libraries or APIs, Grok Build is less likely to suggest patterns that were deprecated last month.
Last updated July 2026. Related: Grok 4.5 full review · The $2.49 vs $11.80 cost analysis · Kimi Code vs Codex vs Claude Code