MAI-DS-R1

By price, MAI-DS-R1 ranks 12th cheapest of 68 on input and 10th on output. Its quality score of 90 ranks 21st of 68, and on value (quality score ÷ output price) it ranks 10th of 68. Its blended rate sits 94% below the catalog average.

In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $21 per month on MAI-DS-R1, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $27. Because output is priced 2.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.

A 128K context window holds roughly 171 pages of A4 text (at ~750 tokens per page), ranking 53rd of 68 here. That covers typical RAG and multi-turn chat, though book-length inputs still need retrieval and chunking. Output runs at about 60 tok/s (55th fastest of 68), acceptable interactively, though long responses will feel slow.

We track 4 Microsoft models, and MAI-DS-R1's blended rate sits 58% above that provider's average. If your task tolerates a little less headroom, Hunyuan HY3 (Tencent) blends about 43% cheaper at a quality score of 87, and is worth benchmarking first. Going the other way, qwen3.5 scores 91 on quality for about 36% less.

The closest model in Microsoft's line-up is Llama-3.3-70B-Instruct ($0.10 input / $0.32 output, quality 78). Against it, MAI-DS-R1 scores 12 points higher on quality, runs 40 tok/s slower (about 40%), costs 11% more blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.