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Decision facts

• Mistral Medium 3.5 is #53; Qwen3 VL 235B A22B Instruct is #54 on the same current language board.
• Index scores are 57.1 for Mistral Medium 3.5 and 57.0 for Qwen3 VL 235B A22B Instruct. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
• Both positions use Measured evidence.
• Listed output price per 1M tokens is $7.50 for Mistral Medium 3.5 and $1.90 for Qwen3 VL 235B A22B Instruct. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $6.75 for Mistral Medium 3.5 versus $1.37 for Qwen3 VL 235B A22B Instruct. Qwen3 VL 235B A22B Instruct costs 79.7% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
• Published context is 262,144 tokens for Mistral Medium 3.5 and 262,144 for Qwen3 VL 235B A22B Instruct.
• Weight access differs: Mistral Medium 3.5 is none; Qwen3 VL 235B A22B Instruct is open.
• ModelCap currently lists 1 providers for Mistral Medium 3.5 and 5 for Qwen3 VL 235B A22B Instruct.

These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.