InclusionAI·#55 of 350 on the current board·cheaper than #54 Kimi K2.7 Code
Ling 3.0 Flash VL is a language model from InclusionAI. It ranks #55 of 350 on ModelCap's current board, with an Index score of 64.6, modeled from the publisher's launch results against measured models. Its score range of 46.0–83.1 spans positions #6–#132. It is listed at $0.06 per million input tokens and $0.18 per million output tokens from one provider. It reads up to 131K tokens of context, and its weights are openly downloadable.
Figures as of 24 Oct 2026, 19:14 UTC · download the public dataset · methodology
Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Not yet published: the base model it derives from, admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
inclusionai/ling-3.0-flash-vlOpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
Models within 3 places of #55 on the ModelCap Index.
Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).
The same publisher's other current models with a public Index position.
Ling 3.0 Flash VL holds ModelCap Index position #55 of 350 ranked language models as of 24 October 2026, with an Index score of 64.6 (interval 46.0–83.1); evidence: modeled · peer benchmarks. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
Ling 3.0 Flash VL is listed at $0.06 per 1M input tokens and $0.18 per 1M output tokens as of 24 October 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.21 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
Ling 3.0 Flash VL has a published context window of 131K tokens (131,072). The snapshot lists a 32,768 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is inclusionAI/Ling-3.0-flash-VL on Hugging Face.
One provider serves Ling 3.0 Flash VL through OpenRouter as of 24 October 2026: DeepInfra. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Ling 3.0 Flash VL has published results on 3 public boards tracked by ModelCap as of 24 October 2026: AA Intelligence Index 24.6 (#86 of 132), AA Terminal-Bench 2.1 64.4% (#39 of 124) and AA Humanity's Last Exam 22.0% (#97 of 265). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
Ling 3.0 Flash VL ranks #55 (Index 64.6) and Ling 3.1 Flash ranks #38 (Index 70.9) on the ModelCap Index as of 24 October 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.
Ling 3.0 Flash VL first appeared in the catalogue on 10 Sept 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.