Ling 3.0 Flash VL with Jev
Ling 3.0 Flash VL is a model from inclusionAI, released 2026-09-10. It costs $0.021 per million input tokens and $0.062 per million output tokens, reads up to 262K tokens of context, and writes up to 32,768 tokens in one reply. Through llm11, set model to inclusionai/ling-3.0-flash-vl.
- Input price
- $0.021 / 1M
- Output price
- $0.062 / 1M
- Context window
- 262K tokens
- Max output
- 33K tokens
- Cached input
- $0.004 / 1M
- Released
- 2026-09-10
- Accepts
- text, image, video
- Intelligence index
- 24.6
Read from the provider's prompt cache
Artificial Analysis, via the catalogue
Read from the live catalogue and refreshed daily. At blended list price, 99% of the 332 priced models we can call cost more.
Using Ling 3.0 Flash VL with Jev
Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Ling 3.0 Flash VL does the answering when Jev sends it work, or when you name it yourself. At list price Ling 3.0 Flash VL falls in the llm11-fast band, but no pack routes to it because inclusionAI is not one of the labs the packs draw from. You can still pin it: pass inclusionai/ling-3.0-flash-vl as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for Ling 3.0 Flash VL with and without it, and this page does not invent any. Every response comes with a receipt that names the model that answered and what it cost against your most expensive model, so you can measure the pairing on your own traffic.
What a request costs
List price arithmetic, the same sum a receipt does. llm11 adds nothing per request; the only fee is on buying credits.
| Request | Tokens in / out | One | A thousand |
|---|---|---|---|
| Short chat turn | 500 / 200 | $0.00002 | $0.023 |
| Question over retrieved documents | 4,000 / 500 | $0.00011 | $0.115 |
| Long document summary | 30,000 / 1,000 | $0.00069 | $0.692 |
Cheaper models to try
Nothing cheaper in the routable set has a benchmark score to compare, so there is no fair substitute to list here.
Call it
Same OpenAI request shape. Naming the model pins it, so nothing is routed, and the answer is still checked.
python
from openai import OpenAI
client = OpenAI(base_url="https://www.llm11.com/v1", api_key="llm11_live_...")
res = client.chat.completions.create(
model="inclusionai/ling-3.0-flash-vl",
messages=[{"role": "user", "content": "Hello"}],
)More from inclusionAI
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Ling 3.0 Flash Fin | $0.060 | $0.180 | 262K | |
| Ling 3.0 Flash | $0.021 | $0.063 | 262K |
Questions
- What is Ling 3.0 Flash VL with Jev?
- Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Ling 3.0 Flash VL does the answering when Jev sends it work, or when you name it yourself. At list price Ling 3.0 Flash VL falls in the llm11-fast band, but no pack routes to it because inclusionAI is not one of the labs the packs draw from. You can still pin it: pass inclusionai/ling-3.0-flash-vl as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Ling 3.0 Flash VL a System One model?
- No. Ling 3.0 Flash VL answers requests. The System One model is Jev, which decides which model answers each one, so the two do different jobs and llm11 uses both.
- How much does Ling 3.0 Flash VL cost?
- $0.021 per million input tokens and $0.062 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00011, so a thousand of them is about $0.115. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Ling 3.0 Flash VL context window?
- 262,144 tokens, with up to 32,768 tokens in a single reply.
- Does Ling 3.0 Flash VL support tool calling and structured output?
- The catalogue lists tool calling, structured output and reasoning controls.
- Can I use Ling 3.0 Flash VL through llm11?
- Yes. Set model to inclusionai/ling-3.0-flash-vl on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Ling 3.0 Flash VL?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price Ling 3.0 Flash VL falls in the llm11-fast band, but no pack routes to it because inclusionAI is not one of the labs the packs draw from. You can still pin it: pass inclusionai/ling-3.0-flash-vl as model and routing steps aside while verification still runs.
- What is a cheaper alternative to Ling 3.0 Flash VL?
- Nothing cheaper in the routable set has a benchmark score to compare, so there is no fair substitute to list.