GPT-4o vs Ministral 3 3B 2512

Our 12-test comparison (scores come from the payload):

• GPT-4o wins (in our testing): persona consistency 5 vs Ministral 4 (GPT-4o tied for 1st with 36 other models) and agentic planning 4 vs 3 (GPT-4o ranks 16 of 54). These wins matter for character-driven chat, resisting prompt injection, and multi-step goal decomposition.
• Ministral 3 3B 2512 wins (in our testing): constrained rewriting 5 vs GPT-4o 3 (Ministral tied for 1st with 4 others) and faithfulness 5 vs GPT-4o 4 (Ministral tied for 1st with 32 others). That shows Ministral is stronger when you need tight character compression or strict adherence to source material.
• Ties (both models scored the same in our tests): structured output 4, strategic analysis 2, creative problem solving 3, tool calling 4, classification 4, long context 4, safety calibration 1, multilingual 4. For example, both score 4 on tool calling (rank 18 of 54), so function selection and argument accuracy are comparable in practice; both also tie on long context (4) and have very large context windows (GPT-4o 128k, Ministral 131k), which supports retrieval over 30k+ tokens.
• External benchmarks: GPT-4o has external scores in the payload — SWE-bench Verified 31%, MATH Level 5 53.3%, and AIME 2025 6.4% (these are Epoch AI results and not our internal 1–5 scores). Ministral 3 3B 2512 has no external benchmark entries in the payload. Note that GPT-4o’s 31% on SWE-bench Verified places it at rank 12 of 12 in that specific external sample per the payload; use that data point with that sample size in mind. Overall implication: the two models perform similarly across most tasks in our 12-test suite; pick GPT-4o when persona/agentic behavior is crucial, and pick Ministral when you need strict rewriting or higher faithfulness at a fraction of the cost.

Per the payload, GPT-4o charges $10.00 per output mTOK and $2.50 per input mTOK; Ministral 3 3B 2512 charges $0.10 per input and $0.10 per output mTOK. At common volumes (output-only): 1M tokens = 1,000 mTOK → GPT-4o $10,000 vs Ministral $100. 10M tokens → GPT-4o $100,000 vs Ministral $1,000. 100M tokens → GPT-4o $1,000,000 vs Ministral $10,000. If you count balanced input+output traffic (input+output per token): GPT-4o = $12.50/mTOK total → 1M tokens = $12,500; Ministral = $0.20/mTOK → 1M tokens = $200. The cost gap (priceRatio 100 in the payload) is decisive for high-volume applications: startups, SaaS companies, and any product expecting millions of tokens/month should evaluate Ministral for parity on many tasks; teams needing GPT-4o’s specific strengths should budget accordingly.

Choose GPT-4o if: you need stronger persona consistency (5 vs 4) and better agentic planning (4 vs 3), multi-modal inputs with a 128k window, and you can absorb substantially higher costs (output $10/mTOK). Use cases: premium customer-facing chatbots that must maintain a persona, agentic assistants that decompose goals and recover from failures, and multimodal apps where cost is secondary. Choose Ministral 3 3B 2512 if: budget is primary, you require top-tier constrained rewriting (5 vs 3) or strict faithfulness (5 vs 4), and you still want a large context window (131k). Use cases: high-volume document transformation, low-cost vision-to-text pipelines, and production services where token cost dominates the decision.