Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3 8B (Reasoning) | GPT-5 mini (high) |
|---|---|---|
| Input ($/M tokens) | $0.18 | $0.25 |
| Output ($/M tokens) | $2.1 | $2 |
Verdict. GPT-5 mini (high) 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 1.1× the per-million-token cost, GPT-5 mini (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5 mini (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen3 8B (Reasoning) is strongest on Coding Index (9.0), Intelligence Index (8.3). GPT-5 mini (high) leads on Intelligence Index (25.8), Coding Index (15.6).
Speed. On throughput, GPT-5 mini (high) generates tokens at 83 tok/s versus 38 tok/s — about 54% faster. On time-to-first-token, Qwen3 8B (Reasoning) responds in 3810ms vs 89370ms, which matters most for chat-style UIs.
Provider. Alibaba and OpenAI sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while OpenAI 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 8B (Reasoning) costs $36.90 ($443/year); GPT-5 mini (high) costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3 8B (Reasoning) ≈ $5.10/run, GPT-5 mini (high) ≈ $5.25/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3 8B (Reasoning) ≈ $246/run, GPT-5 mini (high) ≈ $250/run. Qwen3 8B (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
Qwen3 8B (Reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.66/M tokens vs $0.69/M for GPT-5 mini (high).
GPT-5 mini (high) wins 2 out of 12 benchmarks compared to 0 for Qwen3 8B (Reasoning). See the detailed benchmark chart above for per-category results.
GPT-5 mini (high) generates tokens faster at 83 tok/s vs 38 tok/s. Qwen3 8B (Reasoning) also has lower time-to-first-token (3.81s vs 89.37s).
Choose based on your priorities: Qwen3 8B (Reasoning) for lower cost, GPT-5 mini (high) for stronger benchmark performance, and GPT-5 mini (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.