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Mistral’s New AI Model Faces Criticism: Pricey, Trailed by Rivals

Mistral AI's pricey new model faces lukewarm reception amid dominant Chinese competition.

  • Mistral AI’s new Mistral Medium 3.5 model, a 128-billion-parameter AI, has been met with underwhelming online reactions.
  • The model is priced at $1.50 per million input tokens and $7.50 per million output tokens, which is significantly higher than comparable, more performant Chinese alternatives.
  • Open-source leaderboards are currently dominated by Chinese models from Alibaba, Zhipu AI, and Xiaomi, leaving Mistral as a lone Western contender in the space.
  • The company is positioning the release as a foundational step toward a future large flagship model.

Paris-based Mistral AI released its latest model, Mistral Medium 3.5, on April 29, unveiling a 128-billion-parameter dense model and new agentic features. However, the launch was met with a wave of tepid online reactions, according to initial reports.

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The release included the core model, remote coding agents, and a new “Work Mode” for its consumer interface. Consequently, Mistral merged three previous models into one unified set of configurable weights. This engineering win, however, is overshadowed by the model’s high cost and competitive standing.

The model scores 77.6% on the SWE-Bench Verified coding test. Meanwhile, Alibaba‘s smaller Qwen 3.6 model scores 72.4% and is free under an Apache 2.0 license, as detailed in the provided data. The open-source leaderboard top spots are held by Chinese models, leaving Mistral as a non-Chinese holdout.

Professor Pedro Domingos questioned the release, asking, “I don’t know what’s worse, for Europe to not be in the AI race or for it to be represented by a laughingstock like Mistral.” Youssof Altoukhi of Yoyo Studios did the math, highlighting the pricing disparity with closed models. Some developers argued open weights offer a durability and self-Hosting advantage for enterprise clients.

Mistral‘s pitch may rely on a geopolitical safety net. European entities with data sovereignty concerns have limited options, as Decrypt previously reported regarding HSBC‘s multi-year deal with the company. Therefore, the model’s appeal lies in being a legally safe, auditable, and self-hostable European solution.

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