Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GLM-4.6V (Reasoning) | Agnes 2.5 Pro Alpha |
|---|---|---|
| Input ($/M tokens) | $0.3 | $0.45 |
| Output ($/M tokens) | $0.9 | $0.9 |
Verdict. Agnes 2.5 Pro Alpha takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Agnes 2.5 Pro Alpha is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Agnes 2.5 Pro Alpha makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GLM-4.6V (Reasoning) is strongest on Intelligence Index (16.9). Agnes 2.5 Pro Alpha leads on Coding Index (58.8), Intelligence Index (39.7).
Speed. On throughput, Agnes 2.5 Pro Alpha generates tokens at 202 tok/s versus 55 tok/s — about 73% faster. On time-to-first-token, Agnes 2.5 Pro Alpha responds in 2860ms vs 3880ms, which matters most for chat-style UIs.
Provider. Z AI and Sapiens AI sell to overlapping but distinct developer audiences: Z AI tends to ship frontier reasoning models with premium positioning, while Sapiens AI often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GLM-4.6V (Reasoning) costs $22.50 ($270/year); Agnes 2.5 Pro Alpha costs $27.00 ($324/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GLM-4.6V (Reasoning) ≈ $3.30/run, Agnes 2.5 Pro Alpha ≈ $4.05/run. At agent/realtime scale (200M input / 100M output per million requests): GLM-4.6V (Reasoning) ≈ $150/run, Agnes 2.5 Pro Alpha ≈ $180/run. GLM-4.6V (Reasoning) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
GLM-4.6V (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.45/M tokens vs $0.56/M for Agnes 2.5 Pro Alpha.
Agnes 2.5 Pro Alpha wins 2 out of 12 benchmarks compared to 0 for GLM-4.6V (Reasoning). See the detailed benchmark chart above for per-category results.
Agnes 2.5 Pro Alpha generates tokens faster at 202 tok/s vs 55 tok/s. However, Agnes 2.5 Pro Alpha has lower time-to-first-token (2.86s vs 3.88s).
Choose based on your priorities: GLM-4.6V (Reasoning) for lower cost, Agnes 2.5 Pro Alpha for stronger benchmark performance, and Agnes 2.5 Pro Alpha for faster generation. For latency-sensitive apps, check the TTFT comparison above.