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ModelCap

Ling 3.1 Flash

NewAPI only

InclusionAI·#75 of 280 on the current board·cheaper than #74 Claude Haiku 4.5

Ling 3.1 Flash is a language model from InclusionAI. It ranks #75 of 280 on ModelCap's current board, with an Index score of 59.8, modeled from its measured predecessor. Its score range of 46.2–73.5 spans positions #28–#128. It is listed free of charge from one provider. It reads up to 262K tokens of context and is available only through an API.

Figures as of 2 Oct 2026, 14:34 UTC · download the public dataset · methodology

ModelCap Index · Current board
59.8#75
Modeled from its measured predecessor · range 46.2–73.5
Market Gravity
21.4
Secondary market signal
Input
Free
per 1M tokens
Output
Free
per 1M tokens
Context
262K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
NovitaFreeFree262K——

Other versions (3)

ModelCap Index · Current board

Methodology
59.8
Modeled from its measured predecessor
Current board
#75 of 280
Score range
46.2–73.5
Rank range
#28–#128
Technical details
Public rank basis
Modeled · succession (architecture)
Evidence label
Modeled · succession · publisher-corpus-prior over 231 held-out anchors (22%); opens from measured predecessor inclusionai/ling-3.0-flash (79%); shrunk 0.6 up toward the measured corpus
Index support
10.0% · weak
Identity binding
Exact catalogue product · inclusionai/inclusionai/ling-3.1-flash · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
0
Qualified Index evidence point
59.8
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
59.8 ± 10.6
Independent share
0%
Shrink toward corpus
+0.6
Optimism haircut
None applied
Method
precision-weighted-v1
Channels fused into this model’s launch placement
ChannelEstimateShare
Publisher corpus prior · not independent
publisher-corpus-prior over 231 held-out anchors
62.2 ± 22.922%
Family succession · not independent
opens from measured predecessor inclusionai/ling-3.0-flash
59.2 ± 12.079%
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)
35.8
Open reach (HF downloads)
—
Surface (context / tools / modalities)
75.3
Freshness
100.0
  • · 1 live provider
  • · Catalogue: context 262144, reasoning, tools
  • · First seen 2026-10-02

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
Estimator abstained

insufficient-artifact-metadata

Feature coverage
86%
Training support
240 models · 137 lineages

insufficient-artifact-metadata. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
22.3
insufficient · 32% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
54.0
Evaluation provenance
0.0

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, 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
21.4
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%
35.8

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

Open reach15%
50.0

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

Freshness5%
100.0

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

Specification

Model ID
inclusionai/ling-3.1-flash
Context window
262K tokens
Max output
33K tokens
Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
Not offered
First seen on OpenRouter
2 Oct 2026

Capabilities

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

Alternatives to Ling 3.1 Flash, by the numbers

Ranked neighbours

Models within 3 places of #75 on the ModelCap Index.

Other ranked InclusionAI models

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

Ling 3.1 Flash: common questions

How does Ling 3.1 Flash rank among AI models?

Ling 3.1 Flash holds ModelCap Index position #75 of 280 ranked language models as of 2 October 2026, with an Index score of 59.8 (interval 46.2–73.5); evidence: modeled · succession. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Ling 3.1 Flash cost per 1M tokens?

Ling 3.1 Flash is listed at Free per 1M input tokens and Free per 1M output tokens as of 2 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 Free 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.

What is the context window of Ling 3.1 Flash?

Ling 3.1 Flash has a published context window of 262K tokens (262,144) and a maximum output of 33K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is Ling 3.1 Flash open-weight?

API only. No downloadable model weights are linked in the current source data; access is through a hosted API or product.

Which API providers serve Ling 3.1 Flash?

One provider serves Ling 3.1 Flash through OpenRouter as of 2 October 2026: Novita. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Ling 3.1 Flash been evaluated on?

Ling 3.1 Flash's Index position rests on the evidence listed on this page; it has no result on the public boards ModelCap tracks as separate leaderboards as of 2 October 2026. The evidence panel names each source and its publication date.

When was Ling 3.1 Flash released?

Ling 3.1 Flash first appeared in the catalogue on 2 Oct 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.