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ModelCap

Qwen2.5 VL 72B Instruct

Official publisher releaseRestricted license

Qwen

Qwen2.5 VL 72B Instruct is a language model from Qwen. It does not hold a position on ModelCap's current board yet; it is placed automatically once its model card or a public benchmark compares it with ranked models. It is listed at $0.80 per million input tokens and $1.00 per million output tokens from one provider. It reads up to 128K tokens of context, and its weights are downloadable under a use-restricted licence.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
—
Index position pending
Market Gravity
20.1
Secondary market signal
Input
$0.80
per 1M tokens
Output
$1.00
per 1M tokens
Context
128K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Parasailfp8$0.80$1.00128Kfp8100.0%

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
ovhcloud
live
$1.01$1.0133K509 ms34.8 tok/s—

Reported evaluation leads (39)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
likaixin/ScreenSpot-Pro
overall
—53.3
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
android_studio_macos
—52.5
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
autocad_windows
—26.5
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
blender_windows
—43.7
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
davinci_macos
—43.2
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
eviews_windows
—90
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
excel_macos
—56.2
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
fruitloops_windows
—35.1
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
illustrator_windows
—19.4
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
inventor_windows
—42.9
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
linux_common_linux
—62
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
macos_common_macos
—53.8
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
matlab_macos
—66.7
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
origin_windows
—32.3
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
photoshop_windows
—60.8
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
powerpoint_windows
—73.2
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
premiere_windows
—40.4
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
pycharm_macos
—53.8
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
quartus_windows
—31.1
Unpinned
not published
Reported
Quarantined
likaixin/ScreenSpot-Pro
solidworks_windows
—40.3
Unpinned
not published
Reported
Quarantined

Showing 20 of 39 rows.

Other versions (1)

ModelCap Index · Current board

Methodology
—
Index position pending
Technical details
Public rank basis
Index position pending (abstained)
Evidence label
Index position pending · peers unresolved
Index support
0.0% · not applicable
Identity binding
Exact catalogue product · qwen/qwen/qwen2.5-vl-72b-instruct · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata Qwen/Qwen2.5-VL-72B-Instruct@89c86200743eec961a297729e7990e8f2ddbc4c5 (not the evaluation revision)
Index observations used
0
Architecture fallback
abstained · 0% coverage · 0 anchors
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)
6.5
Liquidity (providers × uptime)
34.4
Open reach (HF downloads)
—
Surface (context / tools / modalities)
40.0
Freshness
8.6
  • · OpenRouter popularity #232
  • · 1 live provider
  • · Catalogue: context 128000, modalities Text/Image
  • · First seen 2025-02-01

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
41.0
26.5–55.6 uncertainty interval
Excluded from rank
Confidence
76%
Training support
221 models · 129 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.3 MAE

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

Deployment readiness

Metadata index
69.2
partial · 76% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
92.5
Deployability
84.0
Evaluation provenance
0.0

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 activity

Venue coverage
Market Gravity
20.1
OpenRouter weekly popularity
#232 of 339

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%
6.5

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.4

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%
8.6

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

Specification

Model ID
qwen/qwen2.5-vl-72b-instruct
Context window
128K tokens
Declared output cap
115K 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, Image
Outputs
Text
Tokenizer
Qwen
Cached input tokens
$0.40 / 1M
First seen on OpenRouter
1 Feb 2025
Knowledge cutoff
2024-06-30

Capabilities

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

Weights & access

Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.

Access
Restricted license
Licence
qwen
Pinned revision
89c86200743e
Parameters
73.4B
Architecture
Qwen2_5_VLForConditionalGeneration
Model type
qwen2_5_vl
Hugging Face downloads (30d)
101K
Downloads (all time)
7.7M
Likes
666
Repository updated
6 Jun 2025, 02:48 UTC

Qwen2.5 VL 72B Instruct: common questions

How does Qwen2.5 VL 72B Instruct rank among AI models?

Qwen2.5 VL 72B Instruct has no public ModelCap Index position as of 6 November 2026: the snapshot lacks enough matched benchmark evidence, or the identity match is unresolved. Its catalogue facts (price, context, providers) are shown without a rank.

How much does Qwen2.5 VL 72B Instruct cost per 1M tokens?

Qwen2.5 VL 72B Instruct is listed at $0.80 per 1M input tokens and $1.00 per 1M output tokens as of 6 November 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 $2.10 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 Qwen2.5 VL 72B Instruct?

Qwen2.5 VL 72B Instruct has a published context window of 128K tokens (128,000). The snapshot lists a 115,200 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 Qwen2.5 VL 72B Instruct open-weight?

Restricted license (qwen). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is Qwen/Qwen2.5-VL-72B-Instruct on Hugging Face.

Which API providers serve Qwen2.5 VL 72B Instruct?

One provider serves Qwen2.5 VL 72B Instruct through OpenRouter as of 6 November 2026: Parasail. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

When was Qwen2.5 VL 72B Instruct released?

Qwen2.5 VL 72B Instruct first appeared in the catalogue on 1 Feb 2025, with a published knowledge cutoff of 2024-06-30. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.