Grok 3 vs Mistral Small 3.2 24B

All benchmark claims below are from our testing. Summary (wins/ties): Grok 3 wins 10 tests, Mistral Small 3.2 24B wins 1, and they tie on tool calling. Detailed walk-through: - structured output: Grok 3 scores 5 vs Mistral 4 — Grok 3 tied for 1st ("tied for 1st with 24 other models out of 54 tested"), meaning better JSON/schema compliance for production integrations. - strategic analysis: Grok 3 5 vs Mistral 2 — Grok 3 ranks tied for 1st ("tied for 1st with 25 other models out of 54"), so it handles nuanced tradeoffs and numeric reasoning substantially better. - constrained rewriting: Grok 3 3 vs Mistral 4 — Mistral wins and ranks 6 of 53 ("rank 6 of 53"), making Mistral the better choice for aggressive compression/character-limit tasks. - creative problem solving: Grok 3 3 vs Mistral 2 — Grok 3 wins (rank 30 of 54), so it provides more feasible, specific creative ideas in our tests. - faithfulness: Grok 3 5 vs Mistral 4 — Grok 3 tied for 1st ("tied for 1st with 32 other models out of 55"), showing stronger source fidelity in tasks that cannot hallucinate. - classification: Grok 3 4 vs Mistral 3 — Grok 3 tied for 1st ("tied for 1st with 29 other models out of 53"), so routing and labeling are more reliable. - long context: Grok 3 5 vs Mistral 4 — Grok 3 tied for 1st ("tied for 1st with 36 other models out of 55"), meaning better retrieval/accuracy at 30K+ tokens in our tests. - safety calibration: Grok 3 2 vs Mistral 1 — Grok 3 ranks better ("rank 12 of 55 (20 models share this score)" vs Mistral "rank 32 of 55"), so Grok 3 refused more harmful prompts while permitting legitimate ones in our setup. - persona consistency: Grok 3 5 vs Mistral 3 — Grok 3 tied for 1st ("tied for 1st with 36 other models out of 53"), which matters for role-based agents and character-driven chat. - agentic planning: Grok 3 5 vs Mistral 4 — Grok 3 tied for 1st ("tied for 1st with 14 other models out of 54"), indicating stronger goal decomposition and recovery strategies. - tool calling: both score 4 and tie (both show "rank 18 of 54 (29 models share this score)"), so function selection and argument accuracy are comparable in our tests. Practical meaning: Grok 3 is clearly stronger on structured outputs, long-context tasks, classification, faithfulness, persona and planning — the kinds of tasks common in enterprise automation and analytics. Mistral’s clear win is constrained rewriting; otherwise it’s competitive on tool calling but behind on strategic and creative reasoning.

Costs in the payload are per mTok (per 1,000 tokens). Grok 3: input $3/mtok, output $15/mtok. Mistral Small 3.2 24B: input $0.075/mtok, output $0.20/mtok. If you budget for 1M input tokens + 1M output tokens (1M each = 1,000 mTok each): Grok 3 = $3,000 (input) + $15,000 (output) = $18,000; Mistral = $75 + $200 = $275. At 10M in+10M out: Grok 3 = $180,000 vs Mistral = $2,750. At 100M in+100M out: Grok 3 = $1,800,000 vs Mistral = $27,500. The payload also gives a price ratio of 75x. Who cares: startups, high-volume APIs, and consumer apps will almost always prefer Mistral on cost; enterprises doing mission-critical extraction, long-context analytics, or classification may accept Grok 3’s substantially higher spend for higher quality on those benchmarks.

Choose Grok 3 if: - You need best-in-class structured output, faithfulness, long context retrieval, classification, persona consistency, or agentic planning in production. Our tests show Grok 3 wins 10 of 12 benchmarks and ranks tied for 1st in several critical categories. Choose Mistral Small 3.2 24B if: - You operate at scale and cost matters (Mistral’s input $0.075/mtok and output $0.20/mtok). It wins constrained rewriting and ties on tool calling, so it’s a strong value pick for high-volume apps, compression tasks, or cost-sensitive deployments.