{"id":1541,"date":"2026-07-11T17:46:27","date_gmt":"2026-07-11T17:46:27","guid":{"rendered":"https:\/\/convly.ai\/llm-leaderboard\/"},"modified":"2026-07-11T17:46:27","modified_gmt":"2026-07-11T17:46:27","slug":"llm-leaderboard","status":"publish","type":"page","link":"https:\/\/convly.ai\/fr\/llm-leaderboard\/","title":{"rendered":"LLM Leaderboard 2026 \u2014 AI Model Intelligence Index"},"content":{"rendered":"

In 2026, Claude Opus 4.8 tops our intelligence index at 55.7, just ahead of OpenAI’s GPT-5.5 (54.8). Google’s Gemini 3.5 Flash (50.2) and open-weight GLM-5.2 (51.1) sit close behind, with Gemini 3.1 Pro (46.5) and DeepSeek V4 Pro (44.3) rounding out the frontier. The single “best” model depends on how you weigh intelligence against price and speed.<\/strong><\/p>\n

The Intelligence column is a composite 0-100 score based on the Artificial Analysis Intelligence Index v4.1, which blends nine demanding evaluations spanning reasoning, coding, agentic tool use, and scientific knowledge. Higher is smarter \u2014 but a two-point gap at the very top rarely changes real-world output quality, so treat clusters of models as roughly equivalent rather than reading tiny differences as decisive.<\/p>\n

Read intelligence alongside price and speed. A frontier model like Opus 4.8 costs far more per token than DeepSeek V4 Flash (40.3) or GLM-5.2, which deliver 70-90% of the intelligence at a fraction of the cost. For high-volume or latency-sensitive work, a cheaper, faster model usually wins; for the hardest reasoning and agentic tasks, the top of the table earns its premium. Sort by the metric that matches your use case.<\/p>\n