R1 0528 vs Ministral 3 8B 2512

Overview: In our 12-test suite R1 0528 wins 8 tasks, Ministral 3 8B 2512 wins 1, and 3 are ties. Detailed walk-through: 1) Tool calling — R1 5 vs Ministral 4. R1 is tied for 1st (tied with 16 others, rank 1 of 54) while Ministral ranks 18 of 54; this implies R1 is more reliable at function selection, argument accuracy and sequencing in our tests. 2) Faithfulness — R1 5 vs Ministral 4; R1 ties for 1st (rank 1 of 55), so it better sticks to source material and avoids hallucinations in our benchmarks. 3) Long context — R1 5 vs Ministral 4; R1 is tied for 1st (rank 1 of 55) despite a smaller context window (163,840 vs 262,144), meaning R1 retrieved and used 30K+ context more accurately in our tests. 4) Safety calibration — R1 4 vs Ministral 1; R1 ranks 6 of 55 vs Ministral 32 of 55, so R1 more correctly refuses harmful requests while allowing legitimate ones. 5) Agentic planning — R1 5 vs Ministral 3; R1 tied for 1st (rank 1 of 54) indicating stronger goal decomposition and failure recovery in our scenarios. 6) Strategic analysis — R1 4 vs Ministral 3; R1 outperforms on nuanced tradeoff reasoning. 7) Creative problem solving — R1 4 vs Ministral 3; R1 produced more feasible, non-obvious ideas in our tasks. 8) Multilingual — R1 5 vs Ministral 4; R1 ties for 1st (rank 1 of 55), delivering higher parity across languages in our tests. 9) Constrained rewriting — Ministral 5 vs R1 4; Ministral ties for 1st (tied with 4 others), so it handles strict compression/character-limit rewriting better in our evaluation. 10) Structured output — tie 4 vs 4; both scored equally but note a practical quirk: R1 returns empty responses on structured_output and constrained_rewriting in short tasks (see quirks), so test this pattern in your flow. 11) Classification — tie 4 vs 4 (both tied for 1st). 12) Persona consistency — tie 5 vs 5 (both tied for 1st). Additional external math signals: R1 scores 96.6% on MATH Level 5 and 66.4% on AIME 2025 (Epoch AI), supporting its strong quantitative performance in our math-related tasks. Practical implications: R1 is the stronger, higher-quality option for tool-heavy, safety-sensitive, long-context, multilingual, and agentic workflows; Ministral is the pick when constrained rewriting, multimodal input (text+image), and dramatically lower per-token cost dominate requirements. Also note R1 quirks: it uses reasoning tokens (they consume output budget), requires high max_completion_tokens, and can return empty responses on structured_output, constrained_rewriting, and agentic_planning for short prompts — these behavior details materially affect integration.

Output price per 1k tokens: R1 0528 = $2.15, Ministral 3 8B 2512 = $0.15 (price ratio 14.333x). If you pay for outputs only: 1M tokens/month → R1 $2,150 vs Ministral $150; 10M → R1 $21,500 vs Ministral $1,500; 100M → R1 $215,000 vs Ministral $15,000. If you count input+output (R1 $0.50+$2.15=$2.65/mTok; Ministral $0.15+$0.15=$0.30/mTok): 1M → $2,650 vs $300; 10M → $26,500 vs $3,000; 100M → $265,000 vs $30,000. Who should care: any high-volume deployment, consumer product, or cost-sensitive startup — at 10M+ tokens/month the dollar gap becomes budget-defining. Choose R1 only if its benchmark advantages outweigh these recurring costs; choose Ministral for volume-sensitive or multimodal workloads.

Choose R1 0528 if: you prioritize best-in-class tool calling (5 vs 4), faithfulness (5 vs 4), safety (4 vs 1), agentic planning (5 vs 3) or need top long-context retrieval — accept much higher per-token costs and engineer around R1's quirks (requires high max_completion_tokens; may return empty for some short structured tasks). Choose Ministral 3 8B 2512 if: you need the lowest per-token cost ($0.15/output vs $2.15), multimodal (text+image) support, or superior constrained-rewriting (5 vs 4); it’s the practical choice for high-volume, vision-enabled, or budget-constrained deployments.