Ant Group has just released Ling 2.6 1T, an open weights, non-reasoning model with high cost efficiency and a reasonable intelligence tradeoff. Ling 2.6 1T scores 34 on the Artificial Analysis Intelligence Index, a 15-point jump from Ling-1T

Ling 2.6 1T is the latest model from Ant Group’s @TheInclusionAI lab. Ant Group recently released Ling 2.6 Flash, a 104B total parameter non-reasoning model. Ling 2.6 1T’s weights have been publicly released on Hugging Face.

Key takeaways:

➤ Comparable intelligence to similarly sized non-reasoning models: At 1T total parameters, Ling 2.6 1T sits near DeepSeek V3.2 (non-reasoning, 32) and Kimi K2.5 (non-reasoning, 37) in intelligence. This is a marked improvement from Ling-1T, which scores 19 on the Intelligence Index. However, there remains a ~10-point gap to frontier non-reasoning open weights models such as GLM-5.1 (non-reasoning, 44) and Kimi K2.6 (non-reasoning, 43).

➤ Strong performance in scientific reasoning and knowledge: Ling 2.6 1T scores 75% on GPQA and 8% on Humanity’s Last Exam (HLE), indicating solid performance on graduate-level reasoning and knowledge recall tasks. This is comparable to DeepSeek V3.2 (non-reasoning), which achieves 75% on GPQA and 11% on HLE.

➤ Efficient token usage: Ling 2.6 1T uses ~16M output tokens to run the Artificial Analysis Intelligence Index, making it more efficient than MiMo V2 Flash (non-reasoning, ~17M), and significantly more efficient than GLM-5.1 (non-reasoning, ~75M) and Kimi K2.6 (non-reasoning, ~27M)

➤ Strong cost-to-intelligence positioning: At $0.30 per million input tokens and $2.50 per million output tokens on InclusionAI’s first-party API, Ling 2.6 1T costs only ~$95 to run the full Artificial Analysis Intelligence Index. This positions it competitively for large-scale workloads relative to models in a similar intelligence tier.

➤ Relatively weak factual reliability: Ling 2.6 1T scores -51 on AA-Omniscience, our benchmark for factual accuracy and hallucination. This is primarily driven by a high hallucination rate (92%), which is similar to GPT-5.5 (non-reasoning, 91%). However, its 21% accuracy is broadly in line with comparable non-reasoning models.

Additional model details:

➤ Size: 1T total parameters

➤ Pricing: $0.30 / $2.50 per 1M input/output tokens (via Novita API)

➤ License: Weights not yet released

➤ Availability: First-party API through InclusionAI