Real data comparison
Z.ai: GLM 5.2 (batch) vs Poolside: Laguna S 2.1 (free)
On price, Z.ai: GLM 5.2 (batch) is cheaper ($0.11 vs $0.11 per 1M). In real production usage, Z.ai: GLM 5.2 (batch) is used more (rank #4 vs #17 of 291). Across 8 real task categories where both models have classified traffic, Z.ai: GLM 5.2 (batch) handles more of the traffic in 8 of them.
- Z.ai: GLM 5.2 (batch)
- Poolside: Laguna S 2.1 (free)
Head-to-head by real task
Z.ai: GLM 5.2 (batch) leads 8 of 8 shared task categories by real classified traffic share; Poolside: Laguna S 2.1 (free) leads 0. Not a benchmark score - this is what developers actually route to each model for, per OpenRouter's task classification.
| Task | Z.ai: GLM 5.2 (batch) | Poolside: Laguna S 2.1 (free) |
|---|---|---|
| Debugging | 10.6% | 3.3% |
| Frontend & UI | 9.7% | 4.6% |
| Code Generation | 7.2% | 3.0% |
| SQL & Database | 6.6% | 2.8% |
| Repo Scanning | 6.6% | 2.9% |
| File I/O | 5.0% | 2.4% |
| DevOps & Config | 6.2% | 5.6% |
| DevOps | 4.4% | 4.0% |
Usage share over time
- Z.ai: GLM 5.2 (batch)
- Poolside: Laguna S 2.1 (free)
Frequently asked questions
Z.ai: GLM 5.2 (batch) vs Poolside: Laguna S 2.1 (free): which is better quality?
Quality data is unavailable for one or both models.
Z.ai: GLM 5.2 (batch) vs Poolside: Laguna S 2.1 (free): which is cheaper?
Z.ai: GLM 5.2 (batch) is cheaper at $0.11/1M vs $0.11/1M.
Z.ai: GLM 5.2 (batch) vs Poolside: Laguna S 2.1 (free): which is used more?
Z.ai: GLM 5.2 (batch) has higher real OpenRouter usage share (rank #4 vs #17 of 291).
Z.ai: GLM 5.2 (batch) vs Poolside: Laguna S 2.1 (free): which wins more real-world task categories?
Z.ai: GLM 5.2 (batch) handles more traffic in 8 of 8 shared task categories where both models have classified OpenRouter usage.
Source: OpenRouter (openrouter.ai/rankings), as of August 9, 2026.
Benchmark scores: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).
Methodology: smophy.ai/benchmark/methodology
Token counts originate from each provider's own tokenizer and are not directly comparable across providers.