Data as of October 25, 2026 · How the score is built
Released Sep 4, 2026262K contextInclusionAI Ling 3.0 Flash VL model card
Ling 3.0 Flash VL
Decision readingLing 3.0 Flash VL is tracked, but not publicly ranked yet. The profile exposes 0 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Released Sep 4, 2026 — see all recent releases
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- inclusionAI/Ling-3.0-flash-VLInclusionAI Ling 3.0 Flash VL model card
- Context window
- 262KInclusionAI Ling 3.0 Flash VL model card
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- InclusionAI publishes the 124B-total, 5.5B-active natively multimodal MoE (image and video input) under MIT on Hugging Face in BF16, FP8, FP4, and INT4 with a 256K context window and SGLang/vLLM serving recipes.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordInclusionAI Ling 3.0 Flash VL model card
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track Ling 3.0 Flash VL, but no weighted text-model benchmark result is published on the site yet. This page shows the metadata and separate protocol evidence we can verify now; a BenchLM score will appear only if compatible public evaluations land.
Ling 3.0 Flash VL is a open weight model with a 262K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
InclusionAI publishes the 124B-total, 5.5B-active natively multimodal MoE (image and video input) under MIT on Hugging Face in BF16, FP8, FP4, and INT4 with a 256K context window and SGLang/vLLM serving recipes.
InclusionAI’s model card reports a 42 on the a third-party intelligence index for Ling-3.0-flash-VL (September 4, 2026), four points above Ling-3.0-flash, and publishes the multimodal benchmark table only as an image, so BenchLM stores no provider rows and lets the external-signal refresh attach independent values. The row stays unranked.
Ling 3.0 Flash VL sits in the Ling 3.0 family with Ling 3.0 Flash, Ling 3.0 Flash Sante, Ling 3.0 Flash FP8, Ling 3.0 Tiny, Ling 3.0 Flash Fin. The profile has no source-displayable benchmark row yet.
Last updated October 25, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Where to run Ling 3.0 Flash VL by API
3 hosts publish a per-token price for it. DeepInfra has the lowest output rate, $0.18 per million tokens. Prices read from each host’s own pages on October 20, 2026.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| DeepInfra | $0.06 | $0.18 | $0.012 | 131K |
| OpenRouter | $0.06 | $0.18 | $0.012 | 131K |
| Novita AI | $0.075 | $0.22 | $0.015 | 262K |
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does Ling 3.0 Flash VL perform overall in AI benchmarks?
Ling 3.0 Flash VL does not have any source-displayable benchmark rows yet, so this profile does not assign a public score or rank. Documented specifications remain visible, while score-led charts and claims stay unavailable until a published evaluation can be attached to the exact model.
Is Ling 3.0 Flash VL open source?
Ling 3.0 Flash VL is an open-weight model from InclusionAI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to Ling 3.0 Flash VL?
Ling 3.0 Flash VL belongs to the Ling 3.0 family. Related tracked variants include Ling 3.0 Flash, Ling 3.0 Flash Sante, Ling 3.0 Flash FP8, plus 2 more. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does Ling 3.0 Flash VL have full benchmark coverage on BenchLM?
No. Ling 3.0 Flash VL currently has 11 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Ling 3.0 Flash VL?
Ling 3.0 Flash VL has a documented context window of 262K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.