Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | o3-mini | GLM-5.1 (Reasoning) |
|---|---|---|
| Input ($/M tokens) | $1.1 | $1.39 |
| Output ($/M tokens) | $4.4 | $4.4 |
Verdict. GLM-5.1 (Reasoning) 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 mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, GLM-5.1 (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GLM-5.1 (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. o3-mini is strongest on Intelligence Index (19.2). GLM-5.1 (Reasoning) leads on Coding Index (55.8), Intelligence Index (41.0).
Speed. On throughput, o3-mini generates tokens at 221 tok/s versus 79 tok/s — about 64% faster. On time-to-first-token, GLM-5.1 (Reasoning) responds in 1420ms vs 6450ms, which matters most for chat-style UIs.
Provider. OpenAI and Z AI sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Z 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): o3-mini costs $99.00 ($1188/year); GLM-5.1 (Reasoning) costs $107.70 ($1292/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): o3-mini ≈ $14.30/run, GLM-5.1 (Reasoning) ≈ $15.75/run. At agent/realtime scale (200M input / 100M output per million requests): o3-mini ≈ $660/run, GLM-5.1 (Reasoning) ≈ $718/run. o3-mini 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
o3-mini is cheaper overall. Its blended price (3:1 input/output ratio) is $1.93/M tokens vs $2.14/M for GLM-5.1 (Reasoning).
GLM-5.1 (Reasoning) wins 2 out of 12 benchmarks compared to 0 for o3-mini. See the detailed benchmark chart above for per-category results.
o3-mini generates tokens faster at 221 tok/s vs 79 tok/s. However, GLM-5.1 (Reasoning) has lower time-to-first-token (1.42s vs 6.45s).
Choose based on your priorities: o3-mini for lower cost, GLM-5.1 (Reasoning) for stronger benchmark performance, and o3-mini for faster generation. For latency-sensitive apps, check the TTFT comparison above.