Grok 3 Mini vs Ministral 3 8B 2512

Across our 12-test suite, Grok 3 Mini wins 4 benchmarks outright, Ministral 3 8B 2512 wins 1, and 7 are ties.

Where Grok 3 Mini leads:

• Tool calling: 5/5 vs 4/5 — Grok 3 Mini ties for 1st among 54 models (17 models share this score); Ministral ranks 18th of 54. For function selection, argument accuracy, and sequencing in agentic workflows, this is a meaningful gap.
• Faithfulness: 5/5 vs 4/5 — Grok 3 Mini ties for 1st among 55 models (33 share this score); Ministral ranks 34th. Sticking to source material without hallucinating matters for RAG pipelines and summarization.
• Long context: 5/5 vs 4/5 — Grok 3 Mini ties for 1st among 55 models (37 share this score); Ministral ranks 38th of 55. At 30K+ token retrieval tasks, Grok 3 Mini handles the depth better — worth noting even though Ministral's context window (262,144 tokens) is twice as large as Grok 3 Mini's (131,072).
• Safety calibration: 2/5 vs 1/5 — Both models score below the median (p50 = 2), but Grok 3 Mini at least reaches it, ranking 12th of 55. Ministral ranks 32nd of 55 at 1/5. Neither excels here; neither should be the primary safety layer in production.

Where Ministral 3 8B 2512 leads:

• Constrained rewriting: 5/5 vs 4/5 — Ministral ties for 1st among 53 models (5 models share this score); Grok 3 Mini ranks 6th. For compression within hard character limits — ad copy, subject lines, social posts — Ministral has a real edge.

Ties across 7 benchmarks: Both models score identically on structured output (4/4), strategic analysis (3/5), creative problem solving (3/5), classification (4/5), persona consistency (5/5), agentic planning (3/5), and multilingual (4/5). Agentic planning is a notable weak point for both — rank 42 of 54, below the p50 of 4. Neither model should be the backbone of a complex multi-step autonomous agent without additional scaffolding.

Neither model has external benchmark scores (SWE-bench, AIME 2025, MATH Level 5) in the payload.

Grok 3 Mini costs $0.30/MTok input and $0.50/MTok output. Ministral 3 8B 2512 costs $0.15/MTok for both input and output — a flat rate that simplifies budgeting. At 1M output tokens/month, Grok 3 Mini runs $0.50 vs Ministral's $0.15, a $0.35 difference. Scale to 10M tokens and the gap is $3.50; at 100M tokens it's $350/month in output costs alone. Input costs add more: at 100M input tokens, Grok 3 Mini costs $30 vs Ministral's $15. For read-heavy workloads — classification pipelines, document routing, summarization at scale — Ministral 3 8B 2512's uniform $0.15 pricing is a meaningful operational advantage. For developers building agentic systems where tool calling reliability and faithfulness matter, Grok 3 Mini's higher cost may be justified by its benchmark edge.

Choose Grok 3 Mini if you're building agentic or API-integrated workflows where tool calling reliability (5/5, tied 1st of 54) and faithfulness to source material (5/5, tied 1st of 55) are priorities. It also has the edge in long-context retrieval tasks and slightly better safety calibration. The reasoning token support (raw thinking traces accessible) adds value for debugging and transparency in logic-heavy pipelines. Budget $0.30/$0.50 per MTok input/output.

Choose Ministral 3 8B 2512 if cost efficiency is a primary constraint or your workload centers on constrained rewriting — where it ties for 1st of 53 models at 5/5. Its flat $0.15/MTok pricing (input and output) makes it significantly cheaper at scale: roughly 3× lower output cost than Grok 3 Mini. It also supports image input (text+image->text modality) and a 262K token context window, making it a better fit for multimodal or ultra-long-document applications where those features matter.