Ling-3.0-flash
Analysis Summary
Ling-3.0-flash is a value-focused model with a 262K context window, tool use, and function calling. Its measured coding capability makes it relevant to code transformation, technical drafting, SEO automation, and structured production tasks that need reliable output at high volume.
The very low listed pricing supports routing routine traffic away from premium models, particularly for classification, rewriting, extraction, and first-pass technical work. Its weaker agentic profile means it is less suitable for autonomous multi-step workflows where persistent planning and dependable tool execution are essential.
Use Ling-3.0-flash as a volume model and coding specialist with validation around consequential outputs. It is an effective cost-control choice when tasks are well specified and a stronger model can handle escalation cases.
Assessed September 7, 2026
Editorial notes
Ling-3.0-flash delivers strong coding capability at exceptionally low pricing, with a 262K context window, tool use, and function calling. Its agentic results are less developed than its coding profile.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Ling-3.0-flash delivers strong coding capability at exceptionally low pricing, with a 262K context window, tool use, and function calling. Its agentic results are less developed than its coding profile.
How Ling-3.0-flash compares
Ling-3.0-flash ranks #44 of 438 AI models we track for overall intelligence, #73 of 210 for coding, #55 of 192 for agentic tasks. Its 262K-token context window is larger than 71% of the models we list. At $0.02 per million input tokens it is cheaper than 79% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.02 | $0.000021 |
| Output | $0.06 | $0.000063 |
What would Ling-3.0-flash cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 780 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Ling-3.0-flash for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout 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..
Frequently asked questions about Ling-3.0-flash
How much does Ling-3.0-flash cost?
Ling-3.0-flash costs $0.02 per million input tokens and $0.06 per million output tokens.
What is the context window of Ling-3.0-flash?
Ling-3.0-flash has a context window of 262,144 tokens (262K).
Is Ling-3.0-flash good for coding?
On our coding benchmark index, Ling-3.0-flash ranks #73 of 210 models, placing it in the broader range of the field for code generation and debugging.
What can Ling-3.0-flash do?
Ling-3.0-flash supports tool use and function calling.
Who created Ling-3.0-flash?
Ling-3.0-flash is developed by Inclusionai and was released on July 23, 2026.