Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen2.5 Turbo | Ministral 3 14B |
|---|---|---|
| Input ($/M tokens) | $0.05 | $0.2 |
| Output ($/M tokens) | $0.2 | $0.2 |
Verdict. Qwen2.5 Turbo and Ministral 3 14B 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, Ministral 3 14B is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Ministral 3 14B makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen2.5 Turbo is strongest on Intelligence Index (6.4). Ministral 3 14B leads on Coding Index (14.4), Intelligence Index (6.0).
Speed. On throughput, Qwen2.5 Turbo generates tokens at 106 tok/s versus 84 tok/s — about 20% faster. On time-to-first-token, Ministral 3 14B responds in 930ms vs 2200ms, which matters most for chat-style UIs.
Provider. Alibaba and Mistral sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Mistral 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): Qwen2.5 Turbo costs $4.50 ($54/year); Ministral 3 14B costs $9.00 ($108/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen2.5 Turbo ≈ $0.65/run, Ministral 3 14B ≈ $1.40/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen2.5 Turbo ≈ $30/run, Ministral 3 14B ≈ $60/run. Qwen2.5 Turbo 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
Qwen2.5 Turbo is cheaper overall. Its blended price (3:1 input/output ratio) is $0.09/M tokens vs $0.20/M for Ministral 3 14B.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Qwen2.5 Turbo generates tokens faster at 106 tok/s vs 84 tok/s. However, Ministral 3 14B has lower time-to-first-token (0.93s vs 2.20s).
Choose based on your priorities: Qwen2.5 Turbo for lower cost, both perform similarly on benchmarks, and Qwen2.5 Turbo for faster generation. For latency-sensitive apps, check the TTFT comparison above.