Llama 3.3 70B Instruct vs Mistral Small 3.1 24B

Summary of head-to-head results in our testing: Llama wins five benchmarks (creative problem solving 3 vs 2, tool calling 4 vs 1, classification 4 vs 3, safety calibration 2 vs 1, persona consistency 3 vs 2). There are seven ties (structured output 4/4, strategic analysis 3/3, constrained rewriting 3/3, faithfulness 4/4, long context 5/5, agentic planning 3/3, multilingual 4/4). On tool calling Llama scores 4 and ranks 18 of 54 in our ranking (display: "rank 18 of 54 (29 models share this score)"), while Mistral scores 1 and ranks 53 of 54 (Mistral also has a quirk: no_tool calling: true). For classification Llama scores 4 and is tied for 1st with 29 other models out of 53; Mistral scores 3 and ranks 31 of 53. Both models excel at long context (5/5) and are tied for 1st among 55 models there. Practical meaning: Llama will be noticeably better for tasks requiring accurate routing/categorization and multi-step tool-driven workflows; Mistral provides equivalent structural output, faithfulness, multilingual quality, and long-context retrieval. Additional external signal for Llama: on MATH Level 5 (Epoch AI) it scores 41.6% and on AIME 2025 (Epoch AI) it scores 5.1%—these external percentages are supplementary to our internal tests and attributed to Epoch AI.

Per the payload, combined per‑million token cost (input + output) is $0.42 for Llama 3.3 70B Instruct (input $0.10 + output $0.32) and $0.91 for Mistral Small 3.1 24B (input $0.35 + output $0.56). At 1M tokens/month that’s $0.42 vs $0.91; at 10M tokens/month $4.20 vs $9.10; at 100M tokens/month $42.00 vs $91.00. The price ratio is 0.5714, so Llama costs ~57% of Mistral per token. Teams operating at high volume (10M+ tokens/month) should care most about this gap; the savings scale linearly and can exceed tens of thousands of dollars annually at production scale.

Choose Llama 3.3 70B Instruct if you need the best cost-to-performance for chat, classification, tool-driven workflows, or high-volume deployments (it wins 5 benchmarks in our tests and costs $0.42 per 1M tokens). Choose Mistral Small 3.1 24B if you require multimodal inputs (text+image->text) and are willing to pay more per token despite its lack of tool calling and lower scores on creative/problem solving and safety calibration.