GPT-4.1 Mini vs Mistral Small 4

Across our 12-test suite GPT-4.1 Mini wins 3 benchmarks, Mistral Small 4 wins 2, and 7 are ties. Detailed walk-through: - Long context: GPT-4.1 Mini scores 5 vs Mistral 4. GPT-4.1 Mini is tied for 1st (tied with 36 others) on long context, meaning it's a safer pick for retrieval at 30K+ tokens and multi-document tasks. - Structured output: Mistral Small 4 scores 5 vs GPT-4.1 Mini 4; Mistral is tied for 1st (with 24 others) — it better follows JSON/schema constraints and format adherence. - Creative problem solving: Mistral 4 vs GPT-4.1 Mini 3; Mistral ranks 9 of 54 (shared) vs GPT rank 30 — expect more novel, feasible ideas from Mistral on ideation tasks. - Constrained rewriting: GPT-4.1 Mini 4 vs Mistral 3; GPT ranks 6 of 53 (strong) — better at tight compression and character-limited rewriting. - Classification: GPT-4.1 Mini 3 vs Mistral 2; GPT ranks 31 of 53 while Mistral ranks 51 of 53 — GPT is meaningfully better at routing/categorization. - Strategic analysis, tool calling, faithfulness, safety calibration, persona consistency, agentic planning, multilingual: all ties (same numeric scores). For those, both models perform similarly on our tests: e.g., both score 4 on tool calling (rank 18 of 54) and 5 on persona consistency (tied for 1st). Practical interpretation: choose GPT-4.1 Mini if your application depends on massive context windows, classification accuracy, or tight rewriting. Choose Mistral Small 4 for stricter schema compliance and more creative idea generation — and when you need a much lower per-token price.

Costs are per 1,000 tokens (mTok). GPT-4.1 Mini: input $0.40/mTok, output $1.60/mTok. Mistral Small 4: input $0.15/mTok, output $0.60/mTok — a 2.6667× price ratio. Example (50/50 input/output split): for 1M tokens/month GPT-4.1 Mini ≈ $1,000; Mistral Small 4 ≈ $375. At 10M tokens/month: GPT-4.1 Mini ≈ $10,000 vs Mistral ≈ $3,750. At 100M tokens/month: GPT-4.1 Mini ≈ $100,000 vs Mistral ≈ $37,500. If your workload is output-heavy, costs rise to $1,600 per 1M tokens for GPT-4.1 Mini vs $600 per 1M for Mistral. High-volume SaaS, consumer apps, and real-time chat providers should care about the multiplier; smaller projects or experimentation budgets will find Mistral substantially cheaper with similar tie-level performance on many benchmarks.

Choose GPT-4.1 Mini if you need: - Very long-context applications (1,047,576 token window) like multi-document retrieval, long transcripts, or chain-of-thought over 30K+ tokens (long context 5 vs 4). - Better classification and constrained rewriting (classification 3 vs 2; constrained rewriting 4 vs 3). Choose Mistral Small 4 if you need: - Reliable structured output / JSON schema compliance (structured output 5 vs 4). - Stronger creative problem-solving (creative problem solving 4 vs 3) and a much lower cost-per-token (input/output are $0.15/$0.60 vs $0.40/$1.60). If budget at scale matters, Mistral gives similar tie-level performance on many dimensions for ~2.67× lower token cost.