Ring-1T is a trillion-parameter sparse mixture-of-experts (MoE) thinking model developed by inclusionAI. It adopts the Ling 2.0 architecture and is trained on the Ling-1T-base foundation model, which contains 1 trillion total parameters with 50 billion activated parameters, supporting a context window of up to 128K tokens. Building upon the preview version released at the end of September, Ring-1T has undergone continued scaling with large-scale verifiable reward reinforcement learning (RLVR) training, further unlocking the natural language reasoning capabilities of the trillion-parameter foundation model.
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77.9%$0.56/ M tokens$2.24/ M tokensRead:0.112/ M tokensWrite:-/ M tokens128K1.17s48.4tps
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ProviderCache Hit RateContext
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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 Consumption
Benchmarks
Scores on standardized evaluations. Higher percentages are better — and rank percentile shows
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Token Ranking
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