Text-to-Image Leaderboard: LMArena Image Model Rankings

Read LMArena rankings for AI models that create pictures from text descriptions. Compare complete model names, scores and votes to choose candidates; no picture or image description is needed to read the rankings.

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Use Toolmu get-text-to-image-leaderboard-lmarena to read rankings for models that create pictures from text descriptions. Reuse a working Toolmu connection, or follow https://toolmu.com/SKILL.md to connect. Check current requirements, availability and the Credits ceiling, then execute within my authorization and budget. No image, image description, model reference or named input is required from me; handle the request internally without inventing generation, filtering, display-count or pagination controls. Apply my ordinary display count only to records actually returned, keeping source order and reporting fewer records if necessary. Show complete readable model names, ranks, scores, votes and actual reference links, retaining real source identities internally and distinguishing versions/configurations. Keep original source ranking ranges and missing details unchanged, without inferring confidence, update time or complete coverage. Keep genuine zero prices separate from missing prices; check currency, image settings, current pricing and license terms independently before using them. This read does not generate pictures, test my image description, confirm model access or establish rights in future images. Bracketed example text is replaced by my own content.

Task:
I am choosing an AI model that creates pictures from text. Read the LMArena rankings and compare the first [number of models to compare, such as three] models returned by name, score, votes and reference link. Explain unavailable information.

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Connection guide

Up to 0.012 credits / call

The final charge is based on confirmed usage. Unused reserved credits return to your available balance.

LMArena

Text-to-Image Leaderboard: LMArena Image Model Rankings

You receive

Your Agent receives a list of image generation model records from Text-to-Image Arena. Each record identifies a model or configuration and provides its source rank, rating and vote count, with a model reference link and any supplied context, release or price information. Ask the Agent to arrange returned records in a comparison table, then use the references to investigate the models you want to test on your own prompts.

Start with your task

I am choosing an AI model that creates pictures from text. Read the LMArena rankings and compare the first [number of models to compare, such as three] models returned by name, score, votes and reference link. Explain unavailable information.

What to know

This Tool retrieves rankings and does not create images. Ratings and votes do not guarantee quality on your prompt, generation access or image usage rights. Records and values may change; the response does not identify a leaderboard update time. Price metadata is incomplete and does not establish a current generation quote.

Inputs & outputs

Inspect the current inputs, availability, and maximum charge before starting.

Input schema

Input schema
Field / Path	Type	Requirement	Meaning
Optional query values`queryParams`	`object`	Optional	No named input is required to read the leaderboard. This optional object allows additional keys, but no prompt, image, model, filter, size, quality or pagination parameter is documented.

View raw JSON

{
  "type": "object",
  "required": [],
  "properties": {
    "queryParams": {
      "type": "object",
      "properties": {},
      "additionalProperties": true
    }
  },
  "additionalProperties": false
}

Result schema

No fixed output contract is available. Field types reflect saved result evidence; individual responses can differ.

Result schema
Field / Path	Type	Meaning
Image model ranking records`result.data.entries`	`array`	A collection of ranked Text-to-Image Arena model records. Compare their identities, ratings, votes and references; the number of returned records can vary.
Source position`result.data.entries[].rank`	`number`	The source’s integer position for a model in this returned comparison. It does not predict the quality of an image generated from your prompt.
Vote count`result.data.entries[].votes`	`number`	The source count associated with the ranked model. Voter identity and counting rules are not supplied, so it does not establish a number of distinct people.
Model rating`result.data.entries[].rating`	`number`	A numerical source value for comparing ranked models. The scale and calculation are not defined here; it is not an evaluation of a prompt you submit.
License label`result.data.entries[].license`	`string`	A source license label for further checking. It does not verify current service access or rights in a generated image.
Model key`result.data.entries[].modelKey`	`string`	The exact source identifier of this returned record. Preserve it with the full display name; it is not a documented request filter or a generation call.
Model reference`result.data.entries[].modelUrl`	`string`	The model reference URL supplied by the source. Use it to investigate the model; it is not a returned image download or proof that generation is currently available.
Rank bound: rankLower`result.data.entries[].rankLower`	`number`	The literal source value labeled rankLower. Its numerical order relative to rankUpper can be reversed. Keep the name and value; no interval method or confidence level is defined.
Rank bound: rankUpper`result.data.entries[].rankUpper`	`number`	The literal source value labeled rankUpper. Read it alongside rankLower without swapping the labels or assuming a conventional statistical interval.
Rating lower value`result.data.entries[].ratingLower`	`number`	A numerical lower value accompanying the source rating. Its estimation method and confidence level are not supplied.
Rating upper value`result.data.entries[].ratingUpper`	`number`	A numerical upper value accompanying the source rating. The endpoint does not define a confidence level or an image-quality range.
Release label`result.data.entries[].releaseType`	`string \| null`	The source may provide a release label such as co_release, or null. Its meaning and the model’s current availability are not established by this lookup.
Context metadata`result.data.entries[].contextLength`	`null \| number`	A source context value that may be null. No unit or counting conditions are defined, so do not interpret it as a verified token, pixel or word capacity.
Image price metadata`result.data.entries[].pricePerImage`	`null \| number`	The source value labeled as an image price. Currency, resolution, quality and billing conditions are unspecified. Keep a literal zero as zero and null as unknown; neither establishes this Tool’s charge or a current generation quote.
Model and configuration name`result.data.entries[].modelDisplayName`	`string`	The complete model name supplied by the source. Preserve any configuration wording so similarly named records remain distinguishable.
Organization`result.data.entries[].modelOrganization`	`string`	The organization string supplied for the model. It may be empty; do not fill an absent value by guessing from a model name or URL.
Input price metadata`result.data.entries[].inputPricePerMillion`	`number \| null`	The source labels this inputPricePerMillion. The priced quantity, currency and conditions are not defined. Null is unknown; zero is a literal value, not a promise of a free current service.
Output price metadata`result.data.entries[].outputPricePerMillion`	`null \| number`	The source labels this outputPricePerMillion. Treat numbers as model metadata and preserve null as unknown; the priced quantity, currency and billing conditions are unspecified.

Additional notes

Keep the complete model display name and model key when making a shortlist. Configuration wording can distinguish similarly named records, so do not merge them into a single family name. Model reference URLs are starting points for further checking; they are not generated image downloads.

Retain rank and rating bounds exactly as returned. The source uses rankLower and rankUpper labels whose numerical order can differ from their names, and it does not supply a statistical method or confidence level. Consider votes and the model’s full identity alongside a small difference in rank.

Image prices, input and output prices, context values and license labels describe model metadata. Missing details do not establish a current quote, capacity or permitted use. The ranking lookup’s own cost is shown in Toolmu’s live price area and is separate from those model price values.

Questions about this tool.

Inputs, results and details to know before running it.

Get connected

Compare the complete model names and any version or configuration wording. Your assistant keeps distinct source records separate, so a similar name is not silently substituted. You do not need to copy an internal model number.

Text-to-Image Leaderboard: LMArena Image Model Rankings

Text-to-Image Leaderboard: LMArena Image Model Rankings

You receive

Start with your task

What to know

Inputs & outputs

Input schema

Result schema

Ask for models that create pictures from text

Choose how many models to compare

Choose models for separate picture tests

Questions about this tool.

You receive

Start with your task

What to know

Inputs & outputs

Input schema

Result schema

Ask for models that create pictures from text

Choose how many models to compare

Choose models for separate picture tests

Questions about this tool.

How do I compare similar model names?

Does a zero image price mean free generation?

Does the license label establish image usage rights?