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Ling 3.0 Flash VL

inclusionAIhuggingface.co/inclusionAI/Ling-3.0-flash-VL

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...

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data quality72

Updated 3 h ago · first seen 11 Sept 2026

model_01M294WVM80NWASNA5CWS68F1R

Overview

Identity

Canonical model
Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
1
API aliases
inclusionai/ling-3.0-flash-vlling-3-0-flash-vlIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Open weights— weights downloadable under MIT; commercial use allowed; redistribution allowed; derivatives allowed; 4 dimensions unknown.

Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.

  • Weights

    Yes

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    Yes

  • Redistribution

    Yes

  • Derivatives

    Yes

Licence: MIT License (permissive · SPDX MIT)

dimensions marked null are unknown, not false

Key facts

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 4 d agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Capabilities

Modalities

Modalities
imagetextvideo
Input
imagetextvideo
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Yes

    OpenRouter public model & pricing listing · T2

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 5 d agomedium

Benchmarks14

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=v4.0 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv4.0reasoningonconditions differ across rows → partially comparable2non-primary groupobs. 15 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=v2.1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv2.1reasoningonconditions differ across rows → partially comparable2non-primary groupobs. 15 Sept 2026artificialanalysis.aiT2
SciCodecoding · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable2−18.9 ptvs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoningonversion4.3conditions differ across rows → partially comparable2−28.4vs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable2−37.2 ptvs Claude Fable 5.1obs. 16 Sept 2026artificialanalysis.aiT2
MMMU-Promultimodal · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningonconditions differ across rows → partially comparable2−7.92 ptvs gpt-6-astraobs. 16 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoningonconditions differ across rows → partially comparable1non-primary groupobs. 16 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond1−10.1 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 14 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing2

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inOutput / 1MStatusObservedSource
OpenRoutercheapest outputinclusionai/ling-3.0-flash-vl:free262.1Kout 32.8K—active43 min agosince 11 Sept 2026openrouter.aiT2
OpenRouterinclusionai/ling-3.0-flash-vl131.1Kout 32.8K$0.012active43 min agosince 11 Sept 2026openrouter.aiT2

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 1 provider

Output price history of Ling 3.0 Flash VL$0$0.05$0.10$0.15$0.20$0.25Sept 26Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $0.18 · 11 Sept 2026OpenRouter: $0.18 → $0 · 11 Sept 2026
  • OpenRouter
  • OpenRouter$0.18 → $011 Sept 2026
  • OpenRouterfirst observed $0.1811 Sept 2026

Input price · USD / 1M tokens 1 provider

Input price history of Ling 3.0 Flash VL$0$0.02$0.04$0.06$0.08Sept 26Sept 26Sept 26Sept 26Sept 26OpenRouter: first observed → $0.06 · 11 Sept 2026OpenRouter: $0.06 → $0 · 11 Sept 2026
  • OpenRouter
  • OpenRouter$0.06 → $011 Sept 2026
  • OpenRouterfirst observed $0.0611 Sept 2026

Hardware fit37

Estimated

19 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit—72.3 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—72.3 GB est.Yes
Apple M2 Ultra4bit—72.3 GB est.Yes
Apple M1 Ultra4bit—72.3 GB est.Yes
Apple M3 Max4bit—72.3 GB est.Yes
Apple M4 Max4bit—72.3 GB est.Yes
Mac Studio (Apple M5 Max)4bit—72.3 GB est.Yes
MacBook Pro (Apple M5 Max)4bit—72.3 GB est.Yes
Apple M2 Max4bit—72.3 GB est.Yes
NVIDIA A100 80GB4bit80 GB72.3 GB est.Yes
NVIDIA H100 SXM4bit80 GB72.3 GB est.Yes
NVIDIA H100 NVL4bit94 GB72.3 GB est.Yes
NVIDIA DGX Spark4bit128 GB72.3 GB est.Yes
NVIDIA H2004bit141 GB72.3 GB est.Yes
NVIDIA H200 NVL4bit141 GB72.3 GB est.Yes
NVIDIA B2004bit180 GB72.3 GB est.Yes
AMD Instinct MI300X4bit192 GB72.3 GB est.Yes
AMD Instinct MI325X4bit256 GB72.3 GB est.Yes
NVIDIA DGX B2004bit1,440 GB72.3 GB est.Yes
Apple M1 Max4bit—72.3 GB est.No
Apple M4 Pro4bit—72.3 GB est.No
Mac mini (Apple M5 Pro)4bit—72.3 GB est.No
MacBook Pro (Apple M5 Pro)4bit—72.3 GB est.No
Apple M3 Pro4bit—72.3 GB est.No
Apple M1 Pro4bit—72.3 GB est.No
Apple M2 Pro4bit—72.3 GB est.No
Apple M44bit—72.3 GB est.No
iMac (Apple M4)4bit—72.3 GB est.No
Mac mini (Apple M6)4bit—72.3 GB est.No
MacBook Air (Apple M5)4bit—72.3 GB est.No
MacBook Pro (Apple M5)4bit—72.3 GB est.No
Apple M24bit—72.3 GB est.No
Apple M34bit—72.3 GB est.No
Apple M14bit—72.3 GB est.No
NVIDIA GeForce RTX 30904bit24 GB72.3 GB est.No
NVIDIA GeForce RTX 40904bit24 GB72.3 GB est.No
NVIDIA GeForce RTX 50904bit32 GB72.3 GB est.No
Assumptions (7)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
  • Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.

Versions & Artifacts0

Version history

Context window2 changes

11 Sept 2026→11 Sept 2026→12 Sept 2026current

Licensefirst observation only

12 Sept 2026current

Max outputfirst observation only

11 Sept 2026current

Opennessfirst observation only

11 Sept 2026current

Parametersfirst observation only

12 Sept 2026current

Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

Artifacts 0

No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.

Timeline15

Full timeline →
  • Benchmark updatedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL on Artificial Analysis Intelligence Index: 24.77 → 24.97

    24.77→24.97artificial_analysis
    artificialanalysis.ai
  • Property changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: hf inference providers changed from ["novita"] to ["deepinfra", "novita"]

    Hf inference providersnovita→deepinfra, novitahuggingface
    huggingface.co
  • Capabilities changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: modalities changed from ["image", "text"] to ["image", "text", "video"]

    Modalitiesimage, text→image, text, videoopenrouter
    openrouter.ai
  • Property changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: modalities input changed from ["image", "text"] to ["image", "text", "video"]

    Input modalitiesimage, text→image, text, videoopenrouter
    openrouter.ai
  • Release date changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: release date changed from 2026-09-10 to 2026-09-04

    Release date10 Sept 2026→4 Sept 2026huggingface
    huggingface.co
  • Capabilities changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: modalities changed from ["image", "text", "video"] to ["image", "text"]

    Modalitiesimage, text, video→image, texthuggingface
    huggingface.co
  • Property changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: modalities input changed from ["image", "text", "video"] to ["image", "text"]

    Input modalitiesimage, text, video→image, texthuggingface
    huggingface.co
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 64.42% on Terminal-Bench

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 0% on Terminal-Bench

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 78.96% on MMMU-Pro

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 44.21% on SciCode

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 21.96% on Humanity's Last Exam

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 86.16% on GPQA Diamond

    artificial_analysis
    artificialanalysis.ai
  • Benchmark resultModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL scores 24.77 on Artificial Analysis Intelligence Index

    artificial_analysis
    artificialanalysis.ai
  • Context window changedModelLing 3.0 Flash VLinclusionAI

    Ling 3.0 Flash VL: context length changed from 262144 to 131072

    Context window262.1K tokens→131.1K tokensopenrouter
    openrouter.ai

Change history

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
1 claims · 1 propertiesShow all properties

Licenselicense1

Claim history for License
ValueValid from → toStatusSourceConfidenceExtractor
MIT → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

40

Source tiers

T240

Freshest observation

3 h ago

Conflicts

None

Source documents 5

Source documents
SourceDocumentTypeTierLast observedSnapshots
OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary43 min ago75
Hugging Face Hub (public pages, model cards, papers)huggingface.co/inclusionAI/Ling-3.0-flash-VL/raw/main/README.md model_cardT2· Quality secondary3 h ago1
Hugging Face Hub (public pages, model cards, papers)huggingface.co/inclusionAI/Ling-3.0-flash-VL model_pageT2· Quality secondary4 h ago24
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=inclusionAI&p=0&sort=downloads listingT2· Quality secondary4 h ago25
Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary5 h ago17

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (72/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →