Ling-1T is a trillion-parameter sparse mixture-of-experts (MoE) model developed by inclusionAI, optimized for efficient and scalable reasoning. Featuring approximately 50 billion active parameters per token, it is pre-trained on over 20 trillion reasoning-dense tokens, supports a 128K context length, and utilizes an Evolutionary Chain-of-Thought (Evo-CoT) process to enhance its reasoning depth. The model achieves state-of-the-art performance across complex benchmarks, demonstrating strong capabilities in code generation, software development, and advanced mathematics. In addition to its core reasoning skills, Ling-1T possesses specialized abilities in front-end code generation—combining semantic understanding with visual aesthetics—and exhibits emergent agentic capabilities, such as proficient tool use with minimal instruction tuning. Its primary use cases span software engineering, professional mathematics, complex logical reasoning, and agent-based workflows that demand a balance of high performance and efficiency.
Providers
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Uptime
24hoursDirect request success rate on AI Gateway and per-provider.
Throughput
24hoursP50 throughput on live AI Gateway traffic, in tokens per second (TPS).
Latency
24hoursP50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.
Activity
Token volume and request traffic to this model over time.
Token volume broken down by the provider that served each request. Larger segments indicate providers handling more of this model's traffic.
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis
Apps
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All
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