Grok 4 vs Mistral Large 3 2512

Across our 12‑test suite Grok 4 wins 6 tests, Mistral Large 3 2512 wins 2, and 4 are ties. Summary by test (score format: Grok → Mistral):

• Structured output: 4 → 5 — Mistral wins. Mistral ranks tied for 1st in structured output (tied with 24 others), so it’s the stronger pick when you must produce strict JSON/schema outputs.
• Agentic planning: 3 → 4 — Mistral wins. Mistral’s rank is 16 of 54 on agentic planning, indicating better goal decomposition and failure recovery in our tests.
• Strategic analysis: 5 → 4 — Grok wins. Grok is tied for 1st on strategic analysis, showing superior nuanced tradeoff reasoning with numbers in our testing.
• Constrained rewriting: 4 → 3 — Grok wins. Grok ranks 6 of 53 here, meaning better compression into strict character limits.
• Classification: 4 → 3 — Grok wins. Grok is tied for 1st with many models on classification; expect more accurate routing/categorization in our tests.
• Long context: 5 → 4 — Grok wins. Grok ties for 1st on long context (tied with 36 others out of 55), so retrieval and instruction fidelity across 30k+ tokens is stronger in our evaluations.
• Safety calibration: 2 → 1 — Grok wins. Grok’s safety calibration rank (12 of 55, tied) indicates a better balance of refusal/accept behavior in our testing.
• Persona consistency: 5 → 3 — Grok wins. Grok is tied for 1st on persona consistency, resisting injection and maintaining character better in our tests.
• Creative problem solving: 3 → 3 — tie. Both scored 3, ranking 30 of 54.
• Tool calling: 4 → 4 — tie. Both rank 18 of 54, so function selection and argument sequencing were comparable in our tests.
• Faithfulness: 5 → 5 — tie. Both top‑score (tied for 1st), meaning both stick to source material in our evaluations.
• Multilingual: 5 → 5 — tie. Both tie for 1st in non‑English output quality. Practical interpretation: pick Mistral when you need reliable schema/JSON outputs and a lower per‑token bill. Pick Grok when long context, classification, strategic reasoning, safety, or persona fidelity materially affect outcomes.

The payload lists per‑mTok rates (per 1,000 tokens): Grok 4 input $3 / output $15; Mistral Large 3 2512 input $0.50 / output $1.50 — a 10× price ratio on both input and output. At realistic volumes (assuming equal input+output):

• 1M input + 1M output tokens (2M tokens): Grok = $18,000 (3k + 15k per 1M → $18k); Mistral = $2,000 ($500 + $1,500).
• 10M in+10M out: Grok ≈ $180,000; Mistral ≈ $20,000.
• 100M in+100M out: Grok ≈ $1,800,000; Mistral ≈ $200,000. The gap matters for any product with millions of tokens per month — cost-sensitive teams and high‑throughput APIs should choose Mistral for price efficiency. Teams where correctness over very long context, tighter safety calibration, or top classification/persona consistency are business‑critical may justify Grok’s substantially higher cost.

Choose Grok 4 if: you need best‑in‑our‑tests long‑context handling (5 vs 4), stronger safety calibration (2 vs 1), top classification (4 vs 3), persona consistency (5 vs 3), or strategic analysis. These capabilities justify Grok’s higher cost for mission‑critical assistants, long‑document workflows, or safety‑sensitive applications. Choose Mistral Large 3 2512 if: you must produce strict structured output (5 vs 4), need better agentic planning (4 vs 3), or you operate at scale and must minimize cost — Mistral is ~10× cheaper per mTok and is the better value for high‑volume APIs and format‑strict integrations.