InclusionAI: Ling 3.0 Tiny
Try Ling 3.0 Tiny for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "inclusionai/ling-3.0-tiny"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "inclusionai/ling-3.0-tiny"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Ling 3.0 Tiny is a small open-weight Mixture-of-Experts model from InclusionAI, the AGI research group at Ant Group. It has 7.9 billion total parameters with 1.3 billion active per token, and a 262,144-token context window. It supports switchable Thinking and Instant modes, so a caller can trade reasoning depth against response speed.
InclusionAI positions it for responsive agents, instruction following, and multi-turn conversations, and it supports native function calling. It is the smallest model in the Ling 3.0 family, below Ling 3.0 Flash (124B total, 5.1B active).
It scores 25 on the Artificial Analysis Intelligence Index. It suits developers who need a low-cost, low-latency model for high-frequency agent and chat requests.
Context Window 262K
tokens
Max Output 33K
tokens
Input Cost $0.02
per million tokens
Output Cost $0.05
per million tokens
Tool Use Yes
Release Date Aug 6, 2026
Output Speed 59
tokens / sec
Latency 3.06s
time to first token
Try Ling 3.0 Tiny for free
Try Ling 3.0 Tiny instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Ling 3.0 Tiny performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 73.4% |
| Humanity's Last Exam Cross-domain reasoning | 9.3% |
| SciCode Scientific programming | 24.2% |
| LCR Long-context reasoning | 60.3% |
Scores sourced from Artificial Analysis.
Find other InclusionAI models →
Ling 3.1 Flash
Ling 3.1 Flash is a Mixture-of-Experts language model from InclusionAI (Ant Group), announced on September 30, 2026 as the next fast-tier model after Ling 3.0 Flash. It has 560 billion total parameters with about 25 billion active per token. InclusionAI positions it for agent tasks, search, office software, and specialist applications. It is designed for a context window of up to one million tokens, while the current free trial is limited to 256,000 tokens. The API accepts reasoning, tool-related, and sampling parameters such as temperature and seed. At the time of the announcement, the benchmark figures came only from Ant Group, and no independent evaluations had been published, so this entry lists no scores. InclusionAI has said it plans to enable the full context window and release the model as open source after the trial. It suits developers who want to test a large, low-cost model for agent and long-document workloads.
ChatLing 3.0 Flash VL
Ling 3.0 Flash VL is InclusionAI's (Ant Group) native multimodal vision-language model, sharing Ling 3.0 Flash's Mixture-of-Experts architecture with 124B total parameters and about 5.5B active per token. It adds image and video understanding through a hybrid backbone mixing Kimi Delta Attention and gated multi-head latent attention layers, plus a VideoRoPE position encoding for tracking motion across video frames. InclusionAI reports the model routes visual input through the same reasoning and self-verification pipeline used for text, spanning object counting, chart and document reading, multi-step reasoning with visual evidence, and interface understanding for task automation. It scores 42 on the Artificial Analysis Intelligence Index (v4.1.1), four points above Ling 3.0 Flash's 38. This paid tier is served at a 131,072-token context (versus 262,144 on the free tier) and supports function calling, useful for agentic workflows like GUI automation or document-analysis agents that combine visual input with tool use.
ChatLing 3.0 Flash
Ling 3.0 Flash is InclusionAI's (Ant Group) successor to Ling 2.6 Flash, a hybrid-reasoning Mixture-of-Experts model with 124B total parameters and about 5.1B active per token. It stacks five Kimi Delta Attention (KDA) layers per one Multi-Head Latent Attention (MLA) layer, combining efficient long-range memory with precise attention, and supports both thinking and non-thinking modes. According to InclusionAI, with roughly 1/8 of the total parameters and 1/12 of the active parameters of its 1T-parameter flagship model, Ling 3.0 Flash matches or beats that flagship on most of the benchmarks the company reported. It natively supports a 262K-token context window, with InclusionAI designing it to scale toward 1M context; the paid tier here is served at 131K context. It targets high-frequency agentic workflows such as coding agents, tool use, document processing, and long multi-turn conversations, where per-token cost and latency matter.
Frequently Asked Questions
You can access Ling 3.0 Tiny by InclusionAI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Ling 3.0 Tiny is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
Ling 3.0 Tiny is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.02 |
| Output | $0.05 |
Ling 3.0 Tiny was created by InclusionAI and released on Aug 6, 2026.
Ling 3.0 Tiny supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.
Ling 3.0 Tiny can generate up to 33K tokens in a single response.
Yes, Ling 3.0 Tiny supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Ling 3.0 Tiny API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add Ling 3.0 Tiny to your app for free
Developers can integrate Ling 3.0 Tiny for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.