{"id":17870,"date":"2026-08-08T08:48:48","date_gmt":"2026-08-08T12:48:48","guid":{"rendered":"https:\/\/wp.glbgpt.com\/?p=17870"},"modified":"2026-08-08T08:48:49","modified_gmt":"2026-08-08T12:48:49","slug":"muse-spark-1-2-review","status":"publish","type":"post","link":"https:\/\/wp.glbgpt.com\/fr\/hub\/muse-spark-1-2-review","title":{"rendered":"Test de Muse Spark 1.2 : tests de performances, API, tarifs et tests de programmation"},"content":{"rendered":"

Muse Spark 1.2 combines unusually low token pricing with a 1M-token context window, and it passed all three base-model coding tasks in our first-attempt API suite.<\/strong> Meta launched the model on 5 ao\u00fbt 2026<\/a>, with a 1 million tokens context window, two API pricing tiers, and a separate terminal agent called Muse Code. Meta\u2019s benchmark results are promising; independent public coding leaderboards have not yet verified the same model-and-agent combinations.<\/p>\n\n\n\n

This review separates the model from the agent, official scores from independent evidence, and standard pricing from the Contributor tier\u2019s data-use trade-off. In our tests, the model completed a Python idempotency fix, a compatibility-preserving TypeScript refactor, and a repository-wide JSONL feature with no retries. Muse Code agent execution was not tested, and tool-call reliability was not tested. If you are comparing the wider field first, our guide to the Les meilleurs mod\u00e8les d'IA pour le codage<\/a> gives the broader competitive context.<\/p>\n\n\n\n

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TRY Muse Spark 1.2 on GlobalGPT!<\/strong><\/a><\/div>\n<\/div>\n\n\n\n