LLM Comparison

GLM-5.3 vs Claude Haiku 5.5: benchmark scores, pricing & comparison.

Side-by-side GLM-5.3 vs Claude Haiku 5.5 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: GLM-5.3 ranks higher (#12 vs #16) and wins 3 of 4 shared benchmarks; Claude Haiku 5.5 costs less ($0.10/$0.50 vs $1.40/$4.40 per 1M tokens).

Rank #12 vs #16AskClash overall scores 63.4 vs 60.0.
Pricing $1.40/$4.40 vs $0.10/$0.50Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryZ.AI vs Anthropic.

GLM-5.3 vs Claude Haiku 5.5 benchmark comparison

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

MetricGLM-5.3Claude Haiku 5.5
Overall Score63.460.0
Leaderboard Rank#12#16
ACB62.263.5
RWT8.5—
HLE62.557.4
GPQA91.7—
SWE-Pro—64.8
Terminal-Bench41.932.8
DeepSWE69.0—
GDPval-AA1769.01620.0
Finance Agent55.8—
Input Price (per 1M tokens)$1.40$0.10
Output Price (per 1M tokens)$4.40$0.50
Context Window1M1M
Benchmarks Published108

GLM-5.3 vs Claude Haiku 5.5 head-to-head charts

GLM-5.3 leads 4 and Claude Haiku 5.5 leads 1 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.

GLM-5.3Claude Haiku 5.5
Overall
63.4GLM-5.3
60.0Claude Haiku 5.5
ACB
62.2GLM-5.3
63.5Claude Haiku 5.5
HLE
62.5GLM-5.3
57.4Claude Haiku 5.5
Terminal-Bench
41.9GLM-5.3
32.8Claude Haiku 5.5
GDPval-AA
1769.0GLM-5.3
1620.0Claude Haiku 5.5
GLM-5.3
Input$1.40
Output$4.40
Workload$2.28
Context1M
Claude Haiku 5.5
Input$0.10
Output$0.50
Workload$0.20
Context1M

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

More GLM-5.3 and Claude Haiku 5.5 comparisons

Explore how GLM-5.3 and Claude Haiku 5.5 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.