Ministral 3 14B 2512 vs Ministral 3 3B 2512
For most developer and consumer AI use cases, choose Ministral 3 14B 2512 for stronger strategic reasoning, creative problem solving, and persona consistency. Ministral 3 3B 2512 is the better value pick — it wins on faithfulness and constrained rewriting and costs half as much.
mistral
Ministral 3 14B 2512
Benchmark Scores
External Benchmarks
Pricing
Input
$0.200/MTok
Output
$0.200/MTok
modelpicker.net
mistral
Ministral 3 3B 2512
Benchmark Scores
External Benchmarks
Pricing
Input
$0.100/MTok
Output
$0.100/MTok
modelpicker.net
Benchmark Analysis
All scores below are from our 12-test suite on a 1–5 scale. Wins/ties follow our reported comparisons. Strategic analysis: Ministral 3 14B 2512 scores 4 vs Ministral 3 3B 2512's 2 — in our testing 14B ranks 27 of 54 while 3B ranks 44 of 54, so 14B is clearly better for nuanced numerical tradeoffs. Constrained rewriting: 3B scores 5 vs 14B's 4 — 3B is tied for 1st on this test, indicating it compresses/rewrites within hard limits more reliably. Structured output: tie at 4/5; both rank similarly (26 of ~54) and will produce comparable JSON/schema-compliant outputs. Long context: tie at 4/5, but 14B has a 262,144-token window versus 3B's 131,072 — same score but 14B supports larger documents in practice. Persona consistency: 14B 5 vs 3B 4 — 14B is tied for the top rank, so it maintains character and resists injection better. Agentic planning: tie at 3/5 for both (rank ~42), so neither is a standout for complex multi-step recovery. Faithfulness: 3B 5 vs 14B 4 — 3B is tied for 1st here, so it sticks to source material with fewer hallucinations in our tests. Classification: tie at 4/5 (both tied for top ranks), so routing and categorization are comparable. Multilingual: tie at 4/5 for both (no practical difference in our tests). Creative problem solving: 14B 4 vs 3B 3 — 14B ranks higher (rank 9 vs rank 30), producing more specific, feasible ideas. Tool calling: tie at 4/5 (both rank 18 of 54), so function selection and argument accuracy are similar. Safety calibration: both score 1/5 and share the same rank, indicating both struggle to balance refusals vs permitted content in our testing. In short: 14B wins on strategic analysis, creative problem solving, and persona consistency; 3B wins on constrained rewriting and faithfulness; the rest are ties.
Pricing Analysis
Per the payload, Ministral 3 14B 2512 charges $0.20 per mTok for input and $0.20 per mTok for output (combined $0.40/mTok). Ministral 3 3B 2512 charges $0.10 input + $0.10 output (combined $0.20/mTok). That means per million tokens processed (input+output): 14B ≈ $400, 3B ≈ $200. At 10M tokens/month: 14B ≈ $4,000 vs 3B ≈ $2,000. At 100M tokens/month: 14B ≈ $40,000 vs 3B ≈ $20,000. Teams with heavy traffic, narrow margins, or large user bases should care about this gap; for small projects or high-value tasks the 14B's higher capabilities can justify the extra $200 per million tokens.
Real-World Cost Comparison
Bottom Line
Choose Ministral 3 14B 2512 if you need better strategic reasoning, higher creative output, stronger persona consistency, or the extra context window (262,144 tokens) — e.g., product copilots handling complex tradeoffs, long-form creative work, or multi-turn character agents. Choose Ministral 3 3B 2512 if budget and inference cost are the priority and you need top-tier constrained rewriting or faithfulness — e.g., high-volume content compression, deterministic rewrites, or deployment where $200 vs $400 per million tokens meaningfully impacts margins.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.