/ Meta / CM3Leon 760M Meta / CM3Leon
CM3Leon 760M 760M retrieval-augmented autoregressive model for interleaved text/image generation and infilling. Paper-documented pretrained size variant.
restricted Closed weights General purpose Image generation
Output resolution 256 × 256 See specification notes below
Output formats Not collected Awaiting source review
Input billing Not collected Meta · research reference
Output billing Not collected No inferred price
Specifications Access & pricing Caching Evaluation Sources & lifecycle
Specifications Provider-documented facts. “Not collected” means we have not verified that field yet, not that the feature is unsupported.
Maximum output Not collected
Reasoning Not collected
Tool calling Not collected
Structured output Not collected
Streaming Not collected
Batch processing Not collected
Fine-tuning Not collected
Knowledge cutoff Not collected
Languages Not collected Context caching Not collected No model-specific inference service or discounted prompt-cache contract is established for these research weights.
Access & pricing Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.
API model ID Not collectedDescriptive catalog identity, not a verified selectable API ID.
Access Paper and examples available. No original public checkpoint or callable inference contract verified.
Regions Research deployment only; public availability and residency are not established Endpoint pricing has not been collected. Check the provider for applicable rates.
Data & enterprise terms The cited research release does not supply a current production processing/retention agreement. Research access or an expired demonstration is not a production API entitlement.
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Caching Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.
01 / INITIAL INPUT Process & retain The system processes eligible input and retains reusable state.
02 / LATER REQUEST Check available state Reuse depends on matching input, session state and the cache policy.
03 / CACHE HIT Reuse & generate Reusing state can reduce repeated work. Any charges follow the billing rules below.
Meta · research reference Not verified No published service cache policy for this research record.
How it works Not collected No published service cache policy for this research record.
Minimum reusable input Not collected No published service cache policy for this research record.
Lifetime & refresh Not collected No published service cache policy for this research record.
How to enable it Not collected No published service cache policy for this research record.
Usage fields Not collected No published service cache policy for this research record.
Billing rules Not collected No published service cache policy for this research record.
Limits & data boundaries Not collected No published service cache policy for this research record.
No verified cache rate for this endpoint. An empty rate is not a zero charge.
What the measurements say
Zero-shot MS-COCO FID-30K Meta research authors · provider-reported 6.61FID Table 1, two retrieved documents; eight generated candidates per input with CLIP selection. Not single-sample performance; lower is better.
Evaluation source (opens in a new tab) Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.
The record behind the model Why it is included Original Meta research weights are not supplied by the reviewed release. The paper documents this named model or explicitly identified trained variant, while public artifacts provide research descriptions, examples or evaluation data rather than an original downloadable checkpoint. This record covers those unreleased research weights, not independently trained reimplementations or openly available base components.
Classification evidence (opens in a new tab) Lifecycle dates Sources reviewed Model notes Nine current/historical Muse identities plus closed-weight research models, trained variants and named pipeline components, including 2026 Text-Audiobox research. API availability is explicitly separated from research references. Regional/private models, historical successors and hosted partner routes remain under review.
Research reference only. No public API selector or model-specific price has been verified. Current Muse tariffs, token limits and processing policies do not apply to this record.
This is Meta CM3Leon, not the later open-weight Chameleon family. Public Metaseq training software does not supply these pretrained model weights.
The July 14 announcement predates the September paper. Sized entries use the date their configurations were formally disclosed rather than claiming separate product launches.
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