Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GLM-4.5-Air | Qwen3 Omni 30B A3B (Reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.17 | $0.25 |
| Output ($/M tokens) | $0.98 | $0.97 |
Verdict. GLM-4.5-Air wins the overall benchmark matchup 1–0 across 1 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Qwen3 Omni 30B A3B (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3 Omni 30B A3B (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GLM-4.5-Air is strongest on Intelligence Index (11.1). Qwen3 Omni 30B A3B (Reasoning) leads on Intelligence Index (7.8).
Speed. On throughput, Qwen3 Omni 30B A3B (Reasoning) generates tokens at 101 tok/s versus 68 tok/s — about 33% faster. On time-to-first-token, Qwen3 Omni 30B A3B (Reasoning) responds in 1910ms vs 2520ms, which matters most for chat-style UIs.
Provider. Z AI and Alibaba sell to overlapping but distinct developer audiences: Z AI tends to ship frontier reasoning models with premium positioning, while Alibaba 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-4.5-Air costs $19.80 ($238/year); Qwen3 Omni 30B A3B (Reasoning) costs $22.05 ($265/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GLM-4.5-Air ≈ $2.81/run, Qwen3 Omni 30B A3B (Reasoning) ≈ $3.19/run. At agent/realtime scale (200M input / 100M output per million requests): GLM-4.5-Air ≈ $132/run, Qwen3 Omni 30B A3B (Reasoning) ≈ $147/run. GLM-4.5-Air 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.
Data from Artificial Analysis API — 12 benchmarks
GLM-4.5-Air is cheaper overall. Its blended price (3:1 input/output ratio) is $0.37/M tokens vs $0.43/M for Qwen3 Omni 30B A3B (Reasoning).
GLM-4.5-Air wins 1 out of 12 benchmarks compared to 0 for Qwen3 Omni 30B A3B (Reasoning). See the detailed benchmark chart above for per-category results.
Qwen3 Omni 30B A3B (Reasoning) generates tokens faster at 101 tok/s vs 68 tok/s. However, Qwen3 Omni 30B A3B (Reasoning) has lower time-to-first-token (1.91s vs 2.52s).
Choose based on your priorities: GLM-4.5-Air for lower cost, GLM-4.5-Air for stronger benchmark performance, and Qwen3 Omni 30B A3B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.