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Muse Spark 1.1

Meta’s original Muse Spark version supports multimodal understanding and reasoning with a 1M-token context and Standard-tier API pricing.

MultimodalReasoning1M context
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At a glance

Know the model before you prompt.

Meta API specifications
Context window
1,048,576 tokens
Maximum output
Not verified
Inputs → output
Text + Images + Video + Audio + PDF → Text
Knowledge cutoff
Not verified

API model ID: muse-spark-1.1

Capabilities & boundaries

What it supports. Where the limits are.

Tool support requires the appropriate API integration; a supported tool is not automatically active in every chat.

Supported API features and tools

  • Long-context multimodal understanding
  • Function/tool calling and structured outputs
  • Web-search grounding through an enabled tool
  • Responses, Chat Completions, and Messages API compatibility
  • Prompt caching
  • Responses API continuation with previous_response_id

Before you choose

  • The max reasoning setting is not supported by this version; it is specific to Standard-tier 1.3.
  • Muse Spark outputs text, not generated images or speech; Meta has separate model families for those outputs.
  • Reasoning cannot be disabled with none, and log probabilities are not supported.
  • No maximum output-token limit or training cutoff is established by the reviewed model documentation.

Choose the reasoning effort

minimallowmediumhighxhigh

Choose minimal, low, medium, high, or xhigh. Omitting the effort parameter uses a model-determined level. Do not send none or assume 1.3’s max setting works on this version. Evaluate the lowest effort that meets your quality checks.

Unsupported settings: none, max.

  • Reasoning tokens and visible answer tokens share the output budget and are both billed as output.
  • Use reasoning.effort with Responses or reasoning_effort with Chat Completions. API compatibility does not guarantee every client feature is supported.
  • For multi-turn reasoning continuity, use Responses with previous_response_id or the documented encrypted reasoning replay. External Chat Completions callers do not receive replayable private reasoning.
  • Meta lists this original version on the Standard tier only; do not invent a 1.1 Contributor model ID.

Put it to work

Start with a more useful prompt.

Original examples from EZ Ai Assist. Adapt these to your task and the features available in your workspace.

Workflow 01

Document an existing code path

Ask for an explanation anchored in the supplied source.

Explain the request lifecycle in the code files below, from entry point to persistence and response. Cite the relevant functions, describe error handling, and identify missing context. Produce a concise onboarding note without proposing a wholesale rewrite or assuming services not shown in the source.

Workflow 02

Inspect a process diagram

Treat visual input as evidence, not executable behavior.

Read this process diagram and list its states, transitions, and decision points. Identify unlabeled branches and ambiguous failure paths. Refer to visible labels in each observation. Finish with questions for the process owner; do not infer that the diagram proves the system actually behaves this way.

Workflow 03

Create a version-comparison rubric

Define a reproducible migration evaluation.

Build an evaluation rubric for migrating this assistant workflow to a newer model version. Use the sample tasks and constraints below. Define correctness checks, tool-permission boundaries, latency targets, and cost measurements. Include failure cases and a rollback threshold without inventing performance scores.

Developer reference

Meta API pricing

These are Meta Standard API reference prices, not EZ Ai Assist subscription prices.

View EZ Ai Assist plans
Standard processing · USD per 1,000,000 tokens
Token typePrice
Input$1.25
Cached input$0.15
Output (including reasoning)$4.25
Additional API fees · USD
UsageRate and unit
Web-search grounding$2.50per 1,000 search queries
  • Meta lists the same Standard token rates for Muse Spark 1.3, 1.2, and 1.1, with no long-context premium.
  • Standard API prompts and completions are not used to train Meta models according to Meta’s pricing documentation. This statement is about direct Meta API terms, not a claim about EZ Ai Assist’s integration.
  • No Contributor tier is listed for Muse Spark 1.1 in the reviewed documentation.
  • Web-search queries add charges beyond token costs; one request can use more than one query. Confirm current rates and inspect response usage before estimating spend.

Common questions

A few things worth knowing.

When should I use Muse Spark 1.1?

Use the original Muse Spark version as a clearly identified option for established integrations and controlled comparisons. New projects should evaluate Meta’s recommended 1.3, while preserving representative test cases before changing versions.

What can this model take as input?

Meta lists text, image, video, audio, and PDF inputs, with text output. Your integration determines which inputs can actually be attached. Understanding an image or recording does not imply image or speech generation.

How does reasoning affect price and latency?

Reasoning tokens count toward the output budget and are billed at the output rate. Higher effort can take longer and leave less room for visible text within the same budget. Muse Spark does not support turning reasoning off with none.

Can I use the max effort setting?

No. Meta documents max only for Standard-tier Muse Spark 1.3. This version supports minimal through xhigh; a missing parameter uses model-determined reasoning rather than a named default.

How is Contributor different from Standard?

The reviewed catalog lists Muse Spark 1.1 on Standard only. Contributor variants exist for 1.2 and 1.3 and permit training on prompts and completions; their prices and IDs must not be attributed to 1.1.

Is Muse Spark an open-weight Llama model?

This guide covers Muse Spark hosted on Meta Model API. Meta’s model overview separately identifies its open-weight offerings; do not assume Muse Spark’s weights, deployment options, or licensing match Llama or another family.

Does this page confirm all these features are available in EZ Ai Assist?

No. It is a provider API reference with original workflow examples. Check the app for model access, input support, tools, reasoning controls, and applicable data terms. EZ Ai Assist plan prices are separate from Meta’s per-token charges.

Check the source

Official documentation

Specifications and API prices checked on . Example prompts and workflow advice are editorial guidance from EZ Ai Assist.

Same provider

More from Meta

Meta

Muse Spark 1.3

Meta’s latest Muse Spark for coding and multi-step tool workflows, with a 1M-token context and max reasoning on the Standard tier.

Meta

Muse Spark 1.2

Meta’s previous Muse Spark version supports text, image, video, audio, and PDF inputs for long-context reasoning and tool-assisted work.