Ling-2.6-1T is an instant (instruct) model from inclusionAI and the company’s trillion-parameter flagship, designed for real-world agents that require fast execution and high efficiency at scale. It uses a “fast...
Model details →inclusionAI: Ling-2.6-1T vs OpenAI: GPT-5 Nano
OpenAI: GPT-5 Nano wins on 5 of 6 axes — pricing and capability skew in its favour for most workloads.
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Model details →Side-by-side comparison
| Capability | inclusionAI: Ling-2.6-1T | OpenAI: GPT-5 Nano | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 262K | 400K | 🏆 OpenAI: GPT-5 Nano |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.07 | $0.05 | 🏆 OpenAI: GPT-5 Nano |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.63 | $0.40 | 🏆 OpenAI: GPT-5 Nano |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | Yes | 🏆 OpenAI: GPT-5 Nano |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | Yes | 🏆 OpenAI: GPT-5 Nano |
Frequently asked questions
Is inclusionAI: Ling-2.6-1T better than OpenAI: GPT-5 Nano?
OpenAI: GPT-5 Nano wins on 5 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between inclusionAI: Ling-2.6-1T and OpenAI: GPT-5 Nano?
Input: $0.07 vs $0.05 per 1M tokens. Output: $0.63 vs $0.40 per 1M tokens.
What context windows do inclusionAI: Ling-2.6-1T and OpenAI: GPT-5 Nano support?
inclusionAI: Ling-2.6-1T supports up to 262K tokens. OpenAI: GPT-5 Nano supports up to 400K tokens.
Do both inclusionAI: Ling-2.6-1T and OpenAI: GPT-5 Nano support tool calling?
inclusionAI: Ling-2.6-1T: yes. OpenAI: GPT-5 Nano: yes.
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