Which model is better: Claude 3.5 Haiku or GLM-5.3?
GLM-5.3 is 56.2% cheaper for input tokens ($0.35 vs. $0.80 per 1M tokens) and $1.00 vs. $4.00 for output tokens (2.3x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (30ms faster than Claude 3.5 Haiku) with 120 vs. 130 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 67.0% vs. 41.6% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
Verified Performance & Unit Economics Delta (12 Dimensions)
Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.
Metric / Dimension
Claude 3.5 Haiku
GLM-5.3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.80
$0.35
GLM-5.3 is 2.3x cheaper
Output Cost / 1M Tokens
$4.00
$1.00
GLM-5.3 (75.0% lower)
Prompt Cache Read / 1M
$0.080
$0.090
Claude 3.5 Haiku is 1.1x cheaper
Prompt Cache Write / 1M
$1.00
$0.35
GLM-5.3 is 2.9x cheaper
Context Window (Max Output)
205k (8k out)
131k (16k out)
Claude 3.5 Haiku (1.6x larger context)
Avg TTFT Response Latency
190ms
160ms
GLM-5.3 (30ms faster)
Generation Speed (Throughput)
130 tok/s
120 tok/s
Claude 3.5 Haiku (+10 tok/s faster)
SWE-bench Verified (Coding)
40.6%
56%
GLM-5.3 (+15.4% lead)
GPQA Diamond (PhD STEM)
41.6%
67%
GLM-5.3 (+25.4% lead)
MMLU-Pro (Multi-Discipline)
71%
80.5%
GLM-5.3 (+9.5% lead)
MATH-500 (Quantitative Logic)
69.4%
88%
GLM-5.3 (+18.6% lead)
Inference Value Score (IVR)
52.4 / 100
69.9 / 100
GLM-5.3 (+17.5 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose GLM-5.3 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M cached reads).
GLM-5.3 is cheaper at $0.35/1M input tokens ($1.00/1M output) compared to $0.80/1M input ($4.00/1M output) for Claude 3.5 Haiku.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.5 Haiku or GLM-5.3?
GLM-5.3 delivers faster first-token latency at 160ms TTFT (120 tok/s throughput) compared to 190ms TTFT (130 tok/s) for Claude 3.5 Haiku.
How do Claude 3.5 Haiku and GLM-5.3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 56% for GLM-5.3. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 67% for GLM-5.3 (and 69.4% vs 88% on MATH-500).
When should you choose Claude 3.5 Haiku?
Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M cached reads).
When should you choose GLM-5.3?
Choose GLM-5.3 (Zhipu AI) for bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution — offering a 131k context window, 160ms TTFT, and $0.35/1M input pricing ($0.090/1M cached reads).
