Grok 3 vs Mistral Small 4

Across our 12-test benchmark suite (scored 1–5), Grok 3 wins 5 benchmarks outright, Mistral Small 4 wins 1, and they tie on 6.

Where Grok 3 leads:

• Strategic Analysis (5 vs 4): Grok 3 scores the maximum in our nuanced tradeoff-reasoning test, ranking tied for 1st among 54 models (with 25 others). Mistral Small 4 scores 4, ranking 27th of 54. For business analysis, scenario planning, or any task requiring structured multi-variable reasoning, Grok 3 has a clear edge here.

• Faithfulness (5 vs 4): In our test of sticking to source material without hallucinating, Grok 3 scores 5 (tied for 1st of 55 models with 32 others). Mistral Small 4 scores 4, ranking 34th of 55. This matters for RAG applications, summarization, and any task where fabrication is costly.

• Classification (4 vs 2): This is the starkest gap in the comparison. Grok 3 scores 4 in our categorization and routing test, tying for 1st of 53 models (with 29 others). Mistral Small 4 scores just 2, ranking 51st of 53 — near the bottom of all models we've tested. If your use case involves routing, tagging, or classification at any scale, this result strongly favors Grok 3.

• Long Context (5 vs 4): Grok 3 scores 5 on retrieval accuracy at 30K+ tokens, tied for 1st of 55 (with 36 others). Mistral Small 4 scores 4, ranking 38th of 55. Note that Mistral Small 4 has a larger context window (262,144 tokens vs Grok 3's 131,072), but the larger window doesn't translate to higher retrieval accuracy in our testing.

• Agentic Planning (5 vs 4): Grok 3 scores 5 on goal decomposition and failure recovery, ranking tied for 1st of 54 (with 14 others — the most selective top-score group in this comparison). Mistral Small 4 scores 4, ranking 16th of 54. For autonomous agents or multi-step pipelines, Grok 3's planning capability is a meaningful advantage.

Where Mistral Small 4 leads:

• Creative Problem Solving (4 vs 3): The one benchmark Mistral Small 4 wins outright. It scores 4 (rank 9 of 54, with 20 others sharing the score) vs Grok 3's 3 (rank 30 of 54). This test measures non-obvious, specific, feasible ideas — relevant for brainstorming, ideation, and open-ended generation tasks.

Where they tie:

• Structured Output (5/5): Both score at the top, tied for 1st of 54 models. JSON schema compliance is a strength for both — neither has an edge here.
• Tool Calling (4/4): Both rank 18th of 54 with 29 models sharing the score. Function selection and argument accuracy are equivalent.
• Multilingual (5/5): Both tied for 1st of 55 models. Non-English quality is excellent for both.
• Persona Consistency (5/5): Both tied for 1st of 53 models.
• Constrained Rewriting (3/3): Both rank 31st of 53. Neither excels at compression within hard character limits.
• Safety Calibration (2/2): Both score 2, ranking 12th of 55. Both sit at the median — neither model stands out for refusing harmful requests or permitting legitimate ones with particular precision.

The pricing gap here is stark. Grok 3 costs $3.00 per million input tokens and $15.00 per million output tokens. Mistral Small 4 costs $0.15 per million input tokens and $0.60 per million output tokens — a 20x gap on input and 25x gap on output.

At 1M output tokens/month, Grok 3 costs $15 vs Mistral Small 4's $0.60 — a $14.40 difference that's easy to absorb.

At 10M output tokens/month, that becomes $150 vs $6 — a $144 monthly gap. Still manageable for teams already paying for infrastructure.

At 100M output tokens/month, the gap is $1,500 vs $60 — a $1,440 monthly difference. At that scale, Mistral Small 4's pricing becomes a serious competitive advantage, especially given that it ties Grok 3 on six of twelve benchmarks and only trails meaningfully on five.

Who should care: Any team running batch jobs, document pipelines, classification at scale, or high-frequency API calls should run the numbers carefully. Grok 3's advantage on faithfulness (5 vs 4) and agentic planning (5 vs 4) may not justify 25x the output cost unless those tasks are mission-critical. For developers prototyping or researchers running experiments, Mistral Small 4's pricing lets you run 25x more tests for the same budget.

Choose Grok 3 if:

• Your application depends on accurate classification or routing — Grok 3 scores 4 vs Mistral Small 4's 2 (near-bottom ranking of 51st of 53 models) in our testing. This is a disqualifying gap for tagging, categorization, or intent detection use cases.
• You're building agentic pipelines: Grok 3's score of 5 on agentic planning (tied for 1st of 54, one of the most selective top groups in our testing) vs Mistral Small 4's 4 matters when failure recovery and multi-step planning are load-bearing.
• Faithfulness to source material is critical (RAG, legal summarization, compliance): Grok 3 scores 5 vs 4 and ranks 1st vs 34th of 55 models.
• You're handling long-document workloads where retrieval accuracy matters more than raw context window size.
• Volume is low enough (under 10M output tokens/month) that the 25x price difference is an acceptable tradeoff for capability.

Choose Mistral Small 4 if:

• Cost is a primary constraint. At $0.60/M output tokens vs $15.00, Mistral Small 4 lets you run 25x more volume for the same budget — a decisive factor at scale.
• Your primary use case is creative or open-ended generation: Mistral Small 4 is the only model that wins a benchmark in this comparison, scoring 4 vs Grok 3's 3 on creative problem solving.
• You need image input alongside text — Mistral Small 4 supports text+image->text modality; Grok 3 is text-only per the payload.
• You want a larger context window: 262,144 tokens vs 131,072 for Grok 3.
• You need the include_reasoning or reasoning parameters, which are available on Mistral Small 4 but not listed for Grok 3 in our data.
• Your workloads tie on the benchmarks that matter to you (structured output, tool calling, multilingual, persona consistency) — in those cases, paying 25x more for Grok 3 offers no measurable return in our testing.