DeepSeek V4.1 Flash 1017 took the lead in traffic
14.9% of traffic over the last 7 days. The previous leader was DeepSeek V4.1 Flash, now at 11.5%.
See DeepSeek V4.1 Flash 1017 on Model Season →14.9% of traffic over the last 7 days. The previous leader was DeepSeek V4.1 Flash, now at 11.5%.
See DeepSeek V4.1 Flash 1017 on Model Season →From $0.37 to $0.78 per 1M tokens, blended. Input $0.040 → $0.200, output $1.35 → $2.50. New price since Oct 23.
What the data says. The model has 0.28% of traffic over the last 7 days, ranked 42nd. Qwen has 1.3% of tokens and 0.6% of estimated spend this week. The lab's most used model is Qwen3.8 Flash, with 0.39% at $0.23 per 1M, and this one costs 3.4 times more.
See Qwen3.8 27B on Model Season →Moonshot AI, $2.00 input and $10.00 output per 1M tokens, 1M context and optional reasoning. No traffic volume measured yet.
What the data says. The model has 0.05% of traffic over the last 7 days, ranked 56th. Moonshot AI has 1.4% of tokens and 4.1% of estimated spend this week. The lab's most used model is Kimi K3, with 1.14% at $2.88 per 1M, and this one costs 1.4 times more.
See Kimi K3.1 Pro on Model Season →From $0.092 to $0.190 per 1M tokens, blended. Input $0.080 → $0.170, output $0.13 → $0.25. New price since Oct 23.
What the data says. No volume over the last 7 days. Its weekly peak was 0.20%. Qwen has 1.3% of tokens and 0.6% of estimated spend this week. The lab's most used model is Qwen3.8 Flash, with 0.39% at $0.23 per 1M, and this one costs 1.2 times less.
See Qwen3.5-9B on Model Season →First volume recorded on Oct 23, 2026, 0 days after entering the catalog, with 0.05% of traffic over the last 7 days.
What the data says. Moonshot AI has 1.4% of tokens and 4.1% of estimated spend this week. The lab's most used model is Kimi K3, with 1.14% at $2.88 per 1M.
See Kimi K3.1 Pro on Model Season →Catalog snapshot of Oct 24, 2026, compared with the previous ones since Oct 17, 2026. Traffic through Oct 23, 2026. Price is a 75% input and 25% output blend, and only becomes news when the new value holds for two snapshots. Order follows a fixed relevance formula that weighs the type of change and the model’s share.