Grok 4 vs Mistral Medium 3.1

Across our 12-test suite, Mistral Medium 3.1 wins 2 benchmarks outright, Grok 4 wins 1, and the two models tie on the remaining 9. Neither model dominates — but where they differ, the differences are meaningful.

Grok 4's win:

• Faithfulness (5/5 vs 4/5): Grok 4 is tied for 1st among 55 tested models; Mistral Medium 3.1 ranks 34th of 55. This is a real gap. Faithfulness measures how closely a model sticks to source material without hallucinating — critical for RAG pipelines, document Q&A, and any task where inventing facts is costly.

Mistral Medium 3.1's wins:

• Agentic Planning (5/5 vs 3/5): Mistral scores tied for 1st among 54 models; Grok 4 ranks 42nd of 54. This is the largest gap in the comparison. Agentic planning tests goal decomposition and failure recovery — the foundation of autonomous agent workflows. Grok 4's 3/5 here is below both the median (4/5) and 75th percentile (5/5) across all models we've tested. If you're building AI agents, this score matters.
• Constrained Rewriting (5/5 vs 4/5): Mistral is tied for 1st among 53 models; Grok 4 ranks 6th of 53. Constrained rewriting tests compression within hard character limits — relevant for headline generation, push notifications, social copy, and any task with strict length requirements.

Ties (same score on both models):

• Strategic Analysis (5/5): Both tied for 1st of 54 — a genuine strength for both.
• Long Context (5/5): Both tied for 1st of 55 — though Grok 4 has a 256K context window versus Mistral's 131K, so it can handle longer documents even if quality at depth is comparable.
• Multilingual (5/5): Both tied for 1st of 55.
• Persona Consistency (5/5): Both tied for 1st of 53.
• Classification (4/5): Both tied for 1st of 53.
• Tool Calling (4/5): Both rank 18th of 54.
• Structured Output (4/5): Both rank 26th of 54.
• Safety Calibration (2/5): Both rank 12th of 55 — both score below the field median on refusing harmful requests while permitting legitimate ones.
• Creative Problem Solving (3/5): Both rank 30th of 54 — both below the median of 4/5.

Note: Neither model has external benchmark scores (SWE-bench Verified, AIME 2025, MATH Level 5) in the payload, so we cannot supplement these results with third-party data.

Grok 4 is priced at $3/M input tokens and $15/M output tokens. Mistral Medium 3.1 is $0.40/M input and $2/M output — making it 7.5x cheaper on output. At real-world usage volumes, that gap compounds fast. At 1M output tokens/month, you're paying $15 for Grok 4 versus $2 for Mistral Medium 3.1 — a $13 difference that's trivial. Scale to 10M output tokens and the gap becomes $150 versus $20, a $130/month difference worth budgeting. At 100M output tokens — typical for a production API serving many users — you're looking at $1,500 versus $200 per month, a $1,300 monthly premium for a model that wins only one of twelve benchmarks. Developers building high-volume pipelines (summarization at scale, bulk classification, document processing) should weight this heavily. Grok 4's pricing makes sense for low-volume, high-stakes tasks where faithfulness to source material is genuinely mission-critical — legal document review, research synthesis, fact-checking workflows. For everything else, the cost argument strongly favors Mistral Medium 3.1.

Choose Mistral Medium 3.1 if:

• You're building agentic or multi-step AI workflows — its 5/5 agentic planning score (tied for 1st of 54) versus Grok 4's 3/5 (42nd of 54) is a substantial edge.
• You need precise constrained rewriting: social copy, headlines, notifications, or any output with hard length limits.
• You're running at volume — 10M+ output tokens/month. Mistral's $2/M output cost versus Grok 4's $15/M saves $130–$1,300/month at scale.
• You want the larger context window to matter less — 131K covers the vast majority of enterprise document tasks.

Choose Grok 4 if:

• Faithfulness to source material is genuinely non-negotiable. Its 5/5 score (tied for 1st of 55) versus Mistral's 4/5 (34th of 55) is the only benchmark where Grok 4 clearly leads.
• You need the 256K context window — twice Mistral's 131K — for very long documents or codebases.
• You need the include_reasoning and logprobs parameters, which Grok 4 supports and Mistral Medium 3.1 does not per the payload.
• Your volume is low enough that the 7.5x output cost premium is immaterial to your budget.