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ModelCap

Ling 3.0 Flash Fin

Official publisher releaseOpen weights

InclusionAI·#111 of 351 on the current board

Ling 3.0 Flash Fin is a language model from InclusionAI. It ranks #111 of 351 on ModelCap's current board, with an Index score of 51.5, carried over from the model it is built on. Its score range of 28.7–74.3 spans positions #30–#234. It reads up to 262K tokens of context, and its weights are openly downloadable.

Figures as of 18 Oct 2026, 03:24 UTC · download the public dataset · methodology

ModelCap Index · Current board
51.5#111
Carried over from the model it is built on · range 28.7–74.3
Market Gravity
12.9
Secondary market signal
Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
262K
tokens
Providers
0
endpoints

Providers

Uptime measured over the last 30 minutes

No provider is currently serving this model.

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
deepinfra
live
$0.06$0.18262K507 ms28.5 tok/stools · structured
novita
live
$0.075$0.22262K933 ms101.5 tok/stools

ModelCap Index · Current board

Methodology
51.5
Carried over from the model it is built on
Current board
#111 of 351
Score range
28.7–74.3
Rank range
#30–#234
Technical details
Public rank basis
Modeled · lineage (lineage)
Evidence label
Modeled · lineage · finetune of inclusionai/ling-3.0-flash · finetune (100%)
Index support
8.0% · weak
Identity binding
Exact catalogue product · inclusionai/inclusionai/ling-3.0-flash-fin · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata inclusionAI/Ling-3.0-flash-Fin@a5b4afb48f526175991724472c179e5a065604de (not the evaluation revision)
Index observations used
0
Qualified Index evidence point
51.5
Verified lineage
inclusionai/ling-3.0-flash · minus 1.2 ( finetune)
How this position was produced · fused launch placement

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.

Fused estimate
51.5 ± 17.8
Independent share
0%
Shrink toward corpus
0.0
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Verified lineage · not independent
finetune of inclusionai/ling-3.0-flash · finetune
51.5 ± 17.8100%
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
—
Liquidity (providers × uptime)
—
Open reach (HF downloads)
58.6
Surface (context / tools / modalities)
75.3
Freshness
82.2
  • · HF 30d downloads 2038
  • · Catalogue: context 262144, reasoning, tools
  • · First seen 2026-08-27

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 capability estimate

Estimate policy
49.7
36.0–63.5 uncertainty interval
Excluded from rank
Confidence
79%
Training support
223 models · 128 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.6 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
71.0
partial · 74% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
70.0
Evaluation provenance
0.0

Not yet published: measured provider uptime, 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 activity

Venue coverage
Market Gravity
12.9
OpenRouter weekly popularity
Not listed

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

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.

Market Gravity breakdown

Usage55%
0.0

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
0.0

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
58.6

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
82.2

Time since first public availability, on a six-month half-life.

Specification

Model ID
inclusionai/ling-3.0-flash-fin
Context window
262K tokens
Declared output cap
33K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.0084 / 1M
First seen on OpenRouter
27 Aug 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Not supported: Structured output
  • Not supported: Response format
  • Not supported: Moderated

Weights & access

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.

Access
Open weights
Licence
mit
Pinned revision
a5b4afb48f52
Parameters
127.5B
Architecture
BailingMoeV3ForCausalLM
Model type
bailing_hybrid
Hugging Face downloads (30d)
2K
Downloads (all time)
4K
Likes
126
Repository updated
24 Sept 2026, 08:53 UTC

Benchmark leaderboards featuring Ling 3.0 Flash Fin

All leaderboards
Public benchmark boards on which Ling 3.0 Flash Fin has a published result
LeaderboardScoreSource rankConfigurationPublished
Artificial Analysis Intelligence IndexArtificial Analysis22.6#91 of 134Reasoning7 Oct 2026
Terminal-Bench 2.1 (Artificial Analysis run)Artificial Analysis62.5%#45 of 128Reasoning1 Oct 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis22.6%#96 of 267Reasoning17 Sept 2026

Alternatives to Ling 3.0 Flash Fin, by the numbers

Ranked neighbours

Models within 3 places of #111 on the ModelCap Index.

Other ranked InclusionAI models

The same publisher's other current models with a public Index position.

Ling 3.0 Flash Fin: common questions

How does Ling 3.0 Flash Fin rank among AI models?

Ling 3.0 Flash Fin holds ModelCap Index position #111 of 351 ranked language models as of 18 October 2026, with an Index score of 51.5 (interval 28.7–74.3); evidence: modeled · lineage. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Ling 3.0 Flash Fin cost per 1M tokens?

No live API price is listed for Ling 3.0 Flash Fin in the current snapshot as of 18 October 2026 because no serving endpoint is published. ModelCap shows a price only when a provider currently lists one.

What is the context window of Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin has a published context window of 262K tokens (262,144). 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.

Is Ling 3.0 Flash Fin open-weight?

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-Fin on Hugging Face.

Which benchmarks has Ling 3.0 Flash Fin been evaluated on?

Ling 3.0 Flash Fin has published results on 3 public boards tracked by ModelCap as of 18 October 2026: AA Intelligence Index 22.6 (#91 of 134), AA Terminal-Bench 2.1 62.5% (#45 of 128) and AA Humanity's Last Exam 22.6% (#96 of 267). 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.

When was Ling 3.0 Flash Fin released?

Ling 3.0 Flash Fin first appeared in the catalogue on 27 Aug 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.