GPT-5.4 Nano vs Ministral 3 8B 2512

Across our 12-test benchmark suite, GPT-5.4 Nano outscores Ministral 3 8B 2512 on 7 tests, loses on 2, and ties on 3.

Where GPT-5.4 Nano wins:

• Structured output (5 vs 4): GPT-5.4 Nano ties for 1st of 54 models (with 24 others); Ministral 3 8B 2512 ranks 26th. This matters for any workflow relying on JSON schema compliance or API response formatting.
• Strategic analysis (5 vs 3): GPT-5.4 Nano ties for 1st of 54; Ministral 3 8B 2512 ranks 36th. A two-point gap on nuanced tradeoff reasoning is significant for use cases like business analysis or decision support.
• Long context (5 vs 4): GPT-5.4 Nano ties for 1st of 55; Ministral 3 8B 2512 ranks 38th. GPT-5.4 Nano also holds a larger context window (400K vs 262K tokens), reinforcing this advantage for document-heavy tasks.
• Multilingual (5 vs 4): GPT-5.4 Nano ties for 1st of 55; Ministral 3 8B 2512 ranks 36th. For global deployments, that score gap reflects meaningfully better non-English output quality in our testing.
• Agentic planning (4 vs 3): GPT-5.4 Nano ranks 16th of 54; Ministral 3 8B 2512 ranks 42nd. Goal decomposition and failure recovery — critical for autonomous agents — clearly favors GPT-5.4 Nano.
• Creative problem solving (4 vs 3): GPT-5.4 Nano ranks 9th of 54; Ministral 3 8B 2512 ranks 30th.
• Safety calibration (3 vs 1): GPT-5.4 Nano ranks 10th of 55; Ministral 3 8B 2512 ranks 32nd with a score of 1 — at the 25th percentile for the field. This means Ministral 3 8B 2512 is more likely to either over-refuse legitimate requests or fail to block harmful ones in our testing.

Where Ministral 3 8B 2512 wins:

• Constrained rewriting (5 vs 4): Ministral 3 8B 2512 ties for 1st of 53 (with 4 others); GPT-5.4 Nano ranks 6th. For compression tasks with hard character limits, Ministral 3 8B 2512 has a genuine edge.
• Classification (4 vs 3): Ministral 3 8B 2512 ties for 1st of 53 (with 29 others); GPT-5.4 Nano ranks 31st. Accurate routing and categorization tasks favor Ministral 3 8B 2512.

Ties (both score equally):

• Tool calling (4/4): Both rank 18th of 54, sharing the score with 28 other models. Neither distinguishes itself here.
• Faithfulness (4/4): Both rank 34th of 55 — mid-field for source adherence.
• Persona consistency (5/5): Both tie for 1st of 53 with 36 other models.

External benchmark: GPT-5.4 Nano scores 87.8% on AIME 2025 (Epoch AI), ranking 8th of 23 models tested on that benchmark. No AIME 2025 score is available for Ministral 3 8B 2512 in the payload. This places GPT-5.4 Nano comfortably above the median (83.9%) for models with AIME scores in our dataset.

GPT-5.4 Nano costs $0.20/MTok input and $1.25/MTok output. Ministral 3 8B 2512 charges a flat $0.15/MTok for both input and output — making it slightly cheaper on input but 8.3x cheaper on output. At 1M output tokens/month, GPT-5.4 Nano costs $1.25 vs $0.15 for Ministral 3 8B 2512 — a $1.10 difference that barely registers. Scale to 10M output tokens and the gap grows to $11 vs $1.50. At 100M output tokens — realistic for a production chatbot, classification pipeline, or document processor — GPT-5.4 Nano runs $1,250 vs $150 for Ministral 3 8B 2512, a $1,100/month difference. Developers building high-throughput applications where output volume dominates costs should weigh that gap carefully. Ministral 3 8B 2512's symmetrical input/output pricing also simplifies cost modeling, since there's no penalty for verbose responses.

Choose GPT-5.4 Nano if:

• Your application depends on structured output or JSON schema compliance — it scores 5/5 and ranks in the top tier on our tests.
• You need strong strategic analysis or multi-step reasoning, where it scores 5 vs Ministral 3 8B 2512's 3.
• You're working with very long documents — 400K context window vs 262K, and a higher long-context benchmark score.
• Agentic or autonomous workflows are in scope — it scores 4 vs 3 on agentic planning and ranks 16th vs 42nd.
• Multilingual output quality matters for your user base.
• Safety calibration is a concern — GPT-5.4 Nano's score of 3 (ranked 10th of 55) is well above Ministral 3 8B 2512's score of 1 (ranked 32nd).
• You need file input support (GPT-5.4 Nano supports text+image+file inputs; Ministral 3 8B 2512 supports text+image).

Choose Ministral 3 8B 2512 if:

• Output volume is high and costs must be minimized — at $0.15/MTok output vs $1.25/MTok, you save $1,100/month at 100M output tokens.
• Your primary use case is classification or routing — it ties for 1st of 53 on classification in our tests.
• Constrained rewriting (e.g., ad copy compression, character-limited summaries) is your core task — it ties for 1st of 53 there.
• You want predictable, symmetrical pricing with no output cost surprise.
• The capability gap on reasoning and planning won't affect your workload.