🤖 AI Summary
OpenRouter’s usage dashboards indicate that Grok has climbed to the top spot as the most popular model on the platform, leading in token consumption and dominating model-share metrics by author and by primary use case. The shift shows up across multiple telemetry slices — overall token usage, per-author share, tool integrations, and even image-processing counts — and is reinforced by several large public apps opting into OpenRouter’s usage tracking. In short, Grok isn’t just getting more calls; it’s being chosen for a wider set of workloads and workflows than competing models.
For the AI/ML community this matters because platform-level adoption shapes downstream tooling, cost dynamics, and where engineers optimize infrastructure and research effort. Higher token share implies real-world preference for Grok’s tradeoffs (latency, cost, instruction-following or multimodal capabilities) and drives ecosystem effects: more adapters, wrappers, benchmarks, and safety evaluations will center on it. The metrics around tool usage and images processed also highlight growing multimodal and tool-enabled patterns (retrieval, function calling, chaining) that practitioners should account for when designing pipelines, estimating inference cost, or prioritizing robustness and alignment testing.
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