Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Ministral 3 14B | gpt-oss-20b (low) |
|---|---|---|
| Input ($/M tokens) | $0.2 | $0.07 |
| Output ($/M tokens) | $0.2 | $0.2 |
Verdict. Ministral 3 14B and gpt-oss-20b (low) 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-oss-20b (low) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). gpt-oss-20b (low) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Ministral 3 14B is strongest on Coding Index (14.4), Intelligence Index (11.2). gpt-oss-20b (low) leads on Intelligence Index (14.4).
Speed. On throughput, gpt-oss-20b (low) generates tokens at 152 tok/s versus 95 tok/s — about 37% faster. On time-to-first-token, Ministral 3 14B responds in 880ms vs 1090ms, which matters most for chat-style UIs.
Provider. Mistral and OpenAI sell to overlapping but distinct developer audiences: Mistral 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): Ministral 3 14B costs $9.00 ($108/year); gpt-oss-20b (low) costs $5.10 ($61/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Ministral 3 14B ≈ $1.40/run, gpt-oss-20b (low) ≈ $0.75/run. At agent/realtime scale (200M input / 100M output per million requests): Ministral 3 14B ≈ $60/run, gpt-oss-20b (low) ≈ $34/run. gpt-oss-20b (low) 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
gpt-oss-20b (low) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.10/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.
gpt-oss-20b (low) generates tokens faster at 152 tok/s vs 95 tok/s. Ministral 3 14B also has lower time-to-first-token (0.88s vs 1.09s).
Choose based on your priorities: gpt-oss-20b (low) for lower cost, both perform similarly on benchmarks, and gpt-oss-20b (low) for faster generation. For latency-sensitive apps, check the TTFT comparison above.