Where is the Ling 3.0 Flash VL documentation?

The Ling 3.0 Flash VL documentation on OpenRouter includes the Best OCR Model for Scanned Documents, Measured blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.

How much does Ling 3.0 Flash VL cost?

Ling 3.0 Flash VL costs $0.06/M input tokens and $0.18/M output tokens, with separate rates for Cache Read at $0.012/M tokens.

What is the context length of Ling 3.0 Flash VL?

Ling 3.0 Flash VL has a 131,072 token context window. It supports up to 32,768 completion tokens.

Does Ling 3.0 Flash VL support tool calling and structured outputs?

Yes. Ling 3.0 Flash VL accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Ling 3.0 Flash VL support?

Ling 3.0 Flash VL accepts text, images, and video as input and returns text.

Which providers serve Ling 3.0 Flash VL?

Ling 3.0 Flash VL is served by 1 provider on OpenRouter: DeepInfra.

What other text models does inclusionAI have?

Ling 3.2 Flash (free), Ling 3.1 Flash, Ling 3.0 Tiny and 1 more are other text models from inclusionAI.

When was Ling 3.0 Flash VL released?

Ling 3.0 Flash VL was released on September 10, 2026.

inclusionAI: Ling 3.0 Flash VL

inclusionai/ling-3.0-flash-vl

Model weights

Compare

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual agent capabilities. Hybrid instant/reasoning model with tool calling.

Modalities

In / out price

$0.06 / $0.18per 1M

Context

131K

Released

Sep 10, 2026

Providers

This model is hosted by one provider. OpenRouter forwards every request without routing.

Latency / throughput


	$0.06	$0.18	$0.012	0.51s	110 tok/s	100.00%

Input $0.06Output $0.18
110 tok/s100.00% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.03164/M tokens

Output

$0.1794/M tokens

Ling 3.0 Flash VL — Price history

Price history

No effective price data for this selection

		$0.0316	$0.179	59.0%	100.0%

Effective in $0.0316Effective out $0.179
Token share
100.0%

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.54%

Availability over the last 3 days

Last 72 hours

Availability 99.54%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

98.85%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for inclusionAI: Ling 3.0 Flash VL (Artificial Analysis)
Source	Benchmark	Score
Artificial Analysis	Ling-3.0-flash-VL Coding Index	57.0
Artificial Analysis	Ling-3.0-flash-VL Agentic Index	28.7
Artificial Analysis	Ling-3.0-flash-VL GPQA Diamond	86.2%
Artificial Analysis	Ling-3.0-flash-VL HLE	22.0%
Artificial Analysis	Ling-3.0-flash-VL AA-LCR	78.3%
Artificial Analysis	Ling-3.0-flash-VL τ-Bench Banking	34.4%
Artificial Analysis	Ling-3.0-flash-VL GDPval-AA	33.4%
Artificial Analysis	Ling-3.0-flash-VL CritPt	2.0%
Artificial Analysis	Ling-3.0-flash-VL SciCode	44.2%
Artificial Analysis	Ling-3.0-flash-VL Terminal-Bench 4.0	0.0%
Artificial Analysis	Ling-3.0-flash-VL Terminal-Bench 2.1	64.4%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

1.22Btokens

Telebot API Service

new

455Mtokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

188Mtokens

Kilo Code

Kilo Code is an open-source AI coding agent that works across VS Code, JetBrains, and CLI to help developers ship code faster with agentic workflows.

134Mtokens

DeepSeek Harness

new

79.4Mtokens

Rest of OpenRouter

225M

Top 5 Apps

78.8M

Not currently available through EU in-region routing. In-region routing docs

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Image

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Image

Ling 3.0 Flash Sante

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Ling 3.0 Flash Fin

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Text262K context

Ling 3.0 Tiny

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Ling 3.0 Flash

Ling-3.0-flash is a 124B-parameter Mixture-of-Experts (MoE) model, with approximately 5.1B parameters activated per token.

The model is designed with token efficiency and production-scale agentic inference as key priorities, enabling developers to complete more useful work within constrained token, latency, and serving-cost budgets.

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Ring-2.6-1T

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With adaptive reasoning effort across high and xhigh modes, Ring-2.6-1T dynamically allocates reasoning budget based on task complexity. This enables stronger performance with lower token overhead, especially in tool-heavy and multi-turn agent workflows.

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Ling-2.6-1T

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The model achieves state-of-the-art results on benchmarks such as AIME26 and SWE-bench Verified, and is well suited for advanced coding, complex reasoning, and large-scale agent workflows where both capability and efficiency are critical.

Text262K context

Ling-2.6-flash

Ling-2.6-flash is an instant (instruct) model from inclusionAI with 104B total parameters and 7.4B active parameters, designed for real-world agents that require fast responses, strong execution, and high token efficiency. It delivers performance comparable to state-of-the-art models at a similar scale while significantly reducing token usage across coding, document processing, and lightweight agent workflows.

Text262K context

inclusionAI: Ling 3.0 Flash VL

Providers