Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3 32B (Non-reasoning) | Granite 4.2 30B |
|---|---|---|
| Input ($/M tokens) | $0.16 | $0.16 |
| Output ($/M tokens) | $0.64 | $0.65 |
Verdict. Granite 4.2 30B 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, Qwen3 32B (Non-reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3 32B (Non-reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen3 32B (Non-reasoning) is strongest on Intelligence Index (8.5). Granite 4.2 30B leads on Coding Index (29.9), Intelligence Index (23.7).
Speed. On throughput, Qwen3 32B (Non-reasoning) generates tokens at 105 tok/s versus 76 tok/s — about 28% faster. On time-to-first-token, Granite 4.2 30B responds in 810ms vs 2470ms, which matters most for chat-style UIs.
Provider. Alibaba and IBM sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while IBM 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): Qwen3 32B (Non-reasoning) costs $14.40 ($173/year); Granite 4.2 30B costs $14.55 ($175/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3 32B (Non-reasoning) ≈ $2.08/run, Granite 4.2 30B ≈ $2.10/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3 32B (Non-reasoning) ≈ $96/run, Granite 4.2 30B ≈ $97/run. Qwen3 32B (Non-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.
Data from Artificial Analysis API — 12 benchmarks
Qwen3 32B (Non-reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.28/M tokens vs $0.28/M for Granite 4.2 30B.
Granite 4.2 30B wins 2 out of 12 benchmarks compared to 0 for Qwen3 32B (Non-reasoning). See the detailed benchmark chart above for per-category results.
Qwen3 32B (Non-reasoning) generates tokens faster at 105 tok/s vs 76 tok/s. However, Granite 4.2 30B has lower time-to-first-token (0.81s vs 2.47s).
Choose based on your priorities: Qwen3 32B (Non-reasoning) for lower cost, Granite 4.2 30B for stronger benchmark performance, and Qwen3 32B (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.