Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3.5 35B A3B (Reasoning) | GPT-5 mini (high) |
|---|---|---|
| Input ($/M tokens) | $0.25 | $0.25 |
| Output ($/M tokens) | $2 | $2 |
Verdict. Qwen3.5 35B A3B (Reasoning) and GPT-5 mini (high) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× 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. Qwen3.5 35B A3B (Reasoning) is strongest on Intelligence Index (29.9). GPT-5 mini (high) leads on Intelligence Index (25.8), Coding Index (15.6).
Speed. On throughput, Qwen3.5 35B A3B (Reasoning) generates tokens at 152 tok/s versus 106 tok/s — about 30% faster. On time-to-first-token, Qwen3.5 35B A3B (Reasoning) responds in 2050ms vs 75020ms, 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): Qwen3.5 35B A3B (Reasoning) costs $37.50 ($450/year); GPT-5 mini (high) costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.5 35B A3B (Reasoning) ≈ $5.25/run, GPT-5 mini (high) ≈ $5.25/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.5 35B A3B (Reasoning) ≈ $250/run, GPT-5 mini (high) ≈ $250/run.
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
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Qwen3.5 35B A3B (Reasoning) generates tokens faster at 152 tok/s vs 106 tok/s. Qwen3.5 35B A3B (Reasoning) also has lower time-to-first-token (2.05s vs 75.02s).
Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and Qwen3.5 35B A3B (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.