Devstral 2 2512 vs Ministral 3 14B 2512

Summary of head-to-head results in our 12-test suite (scores on a 1–5 scale): Wins for Devstral 2 2512 (A):

• structured_output: A 5 vs B 4. In our testing A ties for 1st of 54 models on structured_output, meaning A is top-ranked for JSON/schema compliance and format adherence; B ranks 26 of 54. Expect A to produce more reliably-formatted machine-readable outputs.
• constrained_rewriting: A 5 vs B 4. A is tied for 1st of 53 — better at compressing or rewriting within strict character limits; B ranks 6. Use A when strict-length constraints matter.
• long_context: A 5 vs B 4. A is tied for 1st of 55 for 30K+ retrieval accuracy; B is rank 38. For tasks that require working across very long documents, A is stronger.
• agentic_planning: A 4 vs B 3. A ranks 16 of 54 (tied) vs B at 42; A better decomposing goals and planning recovery in our tests.
• multilingual: A 5 vs B 4. A ties for 1st of 55; B ranks 36. A gives more equivalent-quality non-English output in our testing. Wins for Ministral 3 14B 2512 (B):
• classification: B 4 vs A 3. B ties for 1st of 53 on classification while A is rank 31; B is the clear choice for routing/categorization tasks in our tests.
• persona_consistency: B 5 vs A 4. B ties for 1st of 53; A is rank 38. For strict role-playing and resisting injection in character, B performed better in our testing. Ties in our testing (no clear winner): strategic_analysis 4 vs 4, creative_problem_solving 4 vs 4, tool_calling 4 vs 4, faithfulness 4 vs 4, safety_calibration 1 vs 1. For these tasks both models deliver comparable outcomes based on our scores. Practical meaning: Devstral is the higher-quality option for schema-heavy, long-context and agentic workflows; Ministral is superior where classification and persona maintenance matter, with a much lower token price (output $0.2 vs $2.0 per mTok).

Costs are per mTok (1 mTok = 1,000 tokens). Devstral 2 2512: input $0.40/mTok, output $2.00/mTok. Ministral 3 14B 2512: input $0.20/mTok, output $0.20/mTok. Per-million-token math (1M tokens = 1,000 mTok):

• Devstral input-only: $0.40 × 1,000 = $400; output-only: $2.00 × 1,000 = $2,000. Balanced 50/50 (500 mTok input + 500 mTok output): $1,200 per 1M tokens.
• Ministral input-only: $0.20 × 1,000 = $200; output-only: $0.20 × 1,000 = $200. Balanced 50/50: $400 per 1M tokens. Scale examples (balanced 50/50): 1M tokens/month = Devstral $1,200 vs Ministral $400; 10M = Devstral $12,000 vs Ministral $4,000; 100M = Devstral $120,000 vs Ministral $40,000. Who should care: any high-volume generative workload (10M+ tokens/month) will see a large monthly delta — organizations generating large output volumes or serving many users should prefer Ministral for cost-efficiency unless Devstral’s higher accuracy on structured output/long-context justifies the premium.

Choose Devstral 2 2512 if: you need rock-solid structured outputs (score 5 vs 4), strict constrained rewriting (5 vs 4), or reliable retrieval/processing across 30K+ tokens (long_context 5 vs 4). These advantages matter for code-generation pipelines that require exact JSON, long-document summarization, or multilingual content where correctness is critical. Choose Ministral 3 14B 2512 if: you are cost-sensitive or operating at high token volume and need top-tier classification (4 vs 3) or persona consistency in chat (5 vs 4). Ministral is the pragmatic choice for high-throughput customer routing, chatbots that must maintain a consistent voice, or any product where token cost dominates.