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.
Back to Models
77.9%$0.56/ M tokens$2.24/ M tokensRead:0.112/ M tokensWrite:-/ M tokens128K1.17s48.4tps
Providers
Route requests across multiple providers. Copy a provider slug to set your preference.
ProviderCache Hit RateContext
TboxSunset
theta
Uptime
24hoursDirect request success rate on AI Gateway and per-provider.
Jun 15, 18:29
Tbox100.00%
Throughput
24hoursP50 throughput on live AI Gateway traffic, in tokens per second (TPS).
Jun 15, 18:00
Tbox48.4 tps
Latency
24hoursP50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.
Jun 15, 18:00
Tbox1.17s
Activity
Token volume and request traffic to this model over time.
Token Consumption
Jun 15
Tbox14.4K
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
Artificial 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
Token Ranking
No app usage is available for this period.
Related Models
More models from inclusionAI