Ling 3.1 Flash pricing, plans and limits

Ling 3.1 Flash, InclusionAI's September 2026 release, scored 41 on the Artificial Analysis Intelligence Index, roughly double its predecessor's 20. It suits teams prototyping coding and tool-using agents on a free trial, but anyone needing downloadable weights, vision input or published privacy terms should wait or choose a rival.

Ling 3.1 Flash is a 560-billion-parameter mixture-of-experts reasoning model from InclusionAI, Ant Group's AI lab, that activates about 25 billion parameters per token. It accepts and returns text only, and its trial hosting serves a 262,144-token context while the weights remain unreleased.

Provider: InclusionAI · Family: Ling 3.1

More about InclusionAI on HokAI

Context window: 262,144 tokens · Max output: 32,768

Input modalities: text, tool-calls · Output: text, tool-calls

About Ling 3.1 Flash

InclusionAI, the AI lab inside Ant Group (see InclusionAI), announced Ling-3.1-flash on 30 September 2026, China time. It follows Ling 3.0 Flash from July, which had 124 billion total parameters and about 5.1 billion active, and it sits on a different branch from the finance fine-tune Ling 3.0 Flash Fin. The new model is a sparse mixture of experts with roughly 560 billion total and 25 billion active parameters. InclusionAI positions it for agent tasks, search, office software and specialist applications. The lab's other releases are collected on the InclusionAI provider page.

The independent evidence comes from Artificial Analysis, which ran its ten-evaluation Intelligence Index and scored the model 41. Inside that index it reached 33.3 percent on Terminal-Bench 4.0, 39.4 percent on Humanity's Last Exam and 54.1 percent on SciCode, plus an Elo of 1,622 on GDPval-AA, its test of real knowledge-work deliverables. On AA-Omniscience it answered 29.1 percent of questions correctly and recorded a 37.9 percent hallucination rate, Artificial Analysis's measure of how often a model gives a wrong answer instead of abstaining when it does not know. Third-party write-ups quote higher vendor figures taken from launch graphics we could not inspect, so every score on this page comes from the Artificial Analysis run.

On InclusionAI's own API, Artificial Analysis measured a median 1.79 seconds to the first chunk and about 13.6 seconds end to end on its long-prompt test, of which roughly 9.5 seconds was reasoning before the answer began. The index run consumed about 218 million output tokens, more than twice the 100 million median Artificial Analysis cites for comparable models, and cost about 99 cents per task at the listed rate.

The hosted trial endpoints serve a 256K-token window and up to 32,768 output tokens. InclusionAI says the full 1M-token window arrives when the trial ends and the service turns paid. Input and output are text only, which places it among the text-only models in the directory. Novita AI and OpenRouter expose function calling with tool_choice and a reasoning parameter that is on by default, and Novita adds an Anthropic-style messages endpoint beside chat completions.

On 8 October 2026 the model was free to call on Novita AI, OpenRouter and Vercel AI Gateway. Those are promotional rates, not the list price, so the trial is the place to test before billing starts. The same hosts appear in the AI gateways category, and the AI agent builders category covers the frameworks that would sit in front of an agent model like this one. Compare it with GLM-5.3 Flash, DeepSeek V4.1 Flash, Gemini 3.8 Flash and Claude Haiku 5.5 before committing. On HokAI's own records GLM-5.3 Flash lists a lower rate, a slightly higher index score and MIT-licensed weights; DeepSeek V4.1 Flash lists a lower rate with MIT weights and a slightly lower score; Gemini 3.8 Flash scores about the same, costs more and takes image, audio and video input; Claude Haiku 5.5 lists a lower rate and a higher score. Further up the index, DeepSeek V4 Flash lists a lower rate and a higher score with open weights, Tencent's Hy3 scores far higher at a similarly low rate, and Kimi K3 scores higher at a much higher rate. The model leaderboard sorts all of them on the same index.

InclusionAI says it plans to open-source the model after the trial but has not named a license, a date or a checkpoint format. On 8 October 2026 the expected Hugging Face page at inclusionAI/Ling-3.1-flash returned a 404, Artificial Analysis classes the model as proprietary, HokAI files it as a preview release while the trial runs, its hosted context sits in the 128K to 400K bucket, and we found no system card, data-retention statement or training-data summary. Ling 3.0 Flash and its Fin fine-tune both have public Hugging Face repositories, and the Fin model carries the MIT license, which is a pattern, not a promise.

The sensible use today is a time-boxed trial: run your own terminal and tool-calling tasks while the hosts are free, cap output length because the model is verbose, and decide on the list rate afterwards. Teams that need to self-host, send images or sign a data-processing agreement should look at the peers above until InclusionAI publishes weights and terms.

Screenshots

Pricing

Artificial Analysis recorded a rate of $0.30 per million input tokens and $0.90 per million output tokens, with cached input at $0.06 (an 80% discount). The launch trial is free: Novita AI, OpenRouter and Vercel AI Gateway all showed $0 on 8 October 2026, and InclusionAI described the free period as two weeks, after which the service turns paid. At the listed rate a request of one million input and one million output tokens costs $1.20. [GLM-5.3 Flash](/hub/models/glm-5.3-flash) and [DeepSeek V4.1 Flash](/hub/models/deepseek-v4.1-flash) list lower rates on their HokAI records, so the case for Ling is speed and agent behavior, not price. The model is verbose, which pushes the real bill above a per-token comparison.

What a real job costs

Budgets: 20-page PDF = 30k in / 1k out · Support reply = 2k in / 300 out · Coding agent run = 200k in / 20k out. Computed from the vendor's per-token prices at render time; cached-input discounts are not applied.

Key Features

• Sparse mixture of experts: Only about 4.5% of the weights run for each token, the design choice behind its measured speed.
• Fast output: Artificial Analysis measured a median 211.4 output tokens per second on InclusionAI's own API.
• Reasoning on by default, switchable: Thinking runs unless you turn it off with the reasoning parameter; Artificial Analysis saw about 9.5 seconds of reasoning before the first answer token on its long-prompt test.
• Terminal and tool work: Function calling with tool_choice works on Novita AI and OpenRouter, and the Terminal-Bench 4.0 run scored 33.3%.
• Long-context reasoning: It scored 83% on AA-LCR, Artificial Analysis's long-context reasoning test.
• Anthropic-style endpoint: Novita lists an Anthropic messages endpoint beside chat completions, so Claude-format clients can point at it.

Pros

• Artificial Analysis ran its full ten-evaluation index within days of launch, so the headline score is measured by an outside party, not taken from vendor marketing.
• Speed barely changes between medium and long prompts in Artificial Analysis's tests, which suits long agent loops.
• Free to call on three hosts during the trial, so evaluating it costs only integration time.
• InclusionAI says weights will follow the trial, and its earlier finance fine-tune was published under MIT.

Cons

• Verbose: Artificial Analysis counted about 218 million output tokens on its index run, more than double the 100 million median it cites, which raises real spend on a per-token plan.
• Weights, license, system card and data policy are all unpublished, and no Hugging Face repository existed for it on 8 October 2026.
• Text only: it cannot take images, audio clips or video.
• Hosted trials cap context at 262,144 tokens, a quarter of the 1M design target.

Benchmarks

• GDPval-AA v2: 1,622 cited: Artificial Analysis · 08 Oct 2026 — Real knowledge-work deliverables judged against professionals, run by Artificial Analysis.
• Humanity's Last Exam: 39.4% cited: Artificial Analysis · 08 Oct 2026 — Expert-written questions across many fields, % correct.
• AA Intelligence Index: 41.1 cited: Artificial Analysis · 08 Oct 2026 — Composite of 10 evaluations run by Artificial Analysis, 0 to 100.
• AA blended price: $0.45/M cited: Artificial Analysis · 08 Oct 2026 — Price per 1M tokens at a 3:1 input to output blend, as listed by Artificial Analysis.
• Output speed: 211 tok/s cited: Artificial Analysis · 08 Oct 2026 — Median tokens written per second as measured by Artificial Analysis.

A benchmark is an exam, not the job. Scores transfer unevenly between tasks, so weigh the one closest to your workload and read every figure with its source.

Visit Ling 3.1 Flash Official Page