LLM Comparison

Claude Haiku 5.5 vs Grok 4.7: benchmark scores, pricing & comparison.

Side-by-side Claude Haiku 5.5 vs Grok 4.7 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Verdict: Claude Haiku 5.5 ranks higher (#16 vs #23); Claude Haiku 5.5 costs less ($0.10/$0.50 vs $2.00/$6.00 per 1M tokens).

Rank #16 vs #23AskClash overall scores 60.0 vs 58.1.
Pricing $0.10/$0.50 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs xAI.

Claude Haiku 5.5 vs Grok 4.7 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricClaude Haiku 5.5Grok 4.7
Overall Score60.058.1
Leaderboard Rank#16#23
ACB63.566.4
Coding Agent Index—56.0
HLE57.443.1
SWE-Pro64.8—
SWE-Atlas—63.0
Terminal-Bench32.825.8
DeepSWE—73.0
GDPval-AA1620.01695.2
Finance Agent—49.2
Input Price (per 1M tokens)$0.10$2.00
Output Price (per 1M tokens)$0.50$6.00
Context Window1M500K
Benchmarks Published811

Claude Haiku 5.5 vs Grok 4.7 head-to-head charts

Claude Haiku 5.5 leads 3 and Grok 4.7 leads 2 of 5 shared benchmarks. Claude Haiku 5.5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Haiku 5.5Grok 4.7
Overall
60.0Claude Haiku 5.5
58.1Grok 4.7
ACB
63.5Claude Haiku 5.5
66.4Grok 4.7
HLE
57.4Claude Haiku 5.5
43.1Grok 4.7
Terminal-Bench
32.8Claude Haiku 5.5
25.8Grok 4.7
GDPval-AA
1620.0Claude Haiku 5.5
1695.2Grok 4.7
Claude Haiku 5.5
Input$0.10
Output$0.50
Workload$0.20
Context1M
Grok 4.7
Input$2.00
Output$6.00
Workload$3.20
Context500K

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Claude Haiku 5.5 and Grok 4.7 comparisons

Explore how Claude Haiku 5.5 and Grok 4.7 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.