Meta Muse Spark 1.1 on Mac: Current Status After Muse Spark 1.2

Current status

If you searched for Muse Spark 1.1 on Mac, you have landed in a version transition. Meta still lists muse-spark-1.1 in the Model API, but its current product page now promotes Muse Spark 1.2 as the current generation.¹²³

The central Mac fact has not changed: Muse Spark is not an Apple-Silicon model. Your Mac runs the terminal, editor, browser or agent client. Inference happens remotely through Meta Model API or a gateway provider.

If you need to …	Start with …
begin a new coding project	compare Muse Spark 1.2 first
reproduce an existing 1.1 workflow	pin muse-spark-1.1 explicitly
work offline or keep data on-device	use a local model
grant computer-use or tool permissions	test execution boundaries separately
connect an OpenAI-compatible tool	evaluate Meta API or OpenRouter

What changed after 1.1

The current 1.2 page emphasizes higher first-attempt accuracy and more reliable tool calling for coding workflows. It still lists a 1M-token context window and points developers toward Muse Code, Meta Model API and OpenRouter.²⁴ Meta documents the underlying evaluation setup in a separate methodology note.⁵ The developer documentation’s model overview lists both versions with their context figures.⁶

These figures come from Meta and are not an independent Mac benchmark. For practical use, that means 1.2 is the first candidate for new tests; 1.1 remains the compatibility and historical-comparison option.

What Muse Spark 1.1 actually shipped

Meta describes Muse Spark 1.1 as a multimodal reasoning model for agentic work, coding, tool use and computer use. The model page lists image and document perception alongside long-running agent workflows.¹

The same page publishes comparison values including:

• MCP Atlas: 88.1
• Toolathlon-Verified: 75.6
• OSWorld-Verified: 80.8
• Terminal-Bench 2.1: 80.0
• SWE-Bench Pro: 61.5
• CharXiv Reasoning: 88.4

These numbers come from Meta’s published comparison table. They are not measurements on a Mac, and competitor results were not necessarily produced under identical conditions.¹⁷

Connecting a Mac client to the API

Meta’s current documentation identifies https://api.meta.ai/v1 as the base URL, lists a 1,048,576-token context window and documents OpenAI- and Anthropic-compatible interfaces.⁸ The 1.1 model ID is:

muse-spark-1.1

A client does not install Muse Spark locally. It sends requests to the API. Before using the model in production, check:

1. whether your account is eligible for the 1.1 preview,
2. which API surface your client actually uses,
3. which model ID appears in the request,
4. whether files, images and tool output leave the Mac,
5. how retries, caching and long outputs are billed.

Vercel AI Gateway lists meta/muse-spark-1.1 with a 1M context and $1.25 input/$4.25 output pricing per million tokens.⁹ Gateway availability and provider terms can differ from direct Meta access.

Keep API credentials in a local environment or secret manager. Never put them in a repository, article code block that readers may copy literally, or frontend bundle.

Data use and pricing

Meta’s current API page separates two usage modes. For the standard muse-spark-1.1 model, it lists $1.25 per million input tokens, $0.15 for cached input and $4.25 per million output tokens, and labels the tier “not used to improve our products.”³

The contributor tier is cheaper, but Meta says it is used to improve products and currently lists it for muse-spark-1.2-contributor. This is an operational decision, not a footnote: source code, client documents and internal screenshots need a tier that fits the data policy.

A 1M context window can raise costs quickly. Limit logs, select relevant files and record token use and tool calls. An agent that rereads the same repository five times is not a low-cost workflow just because the per-token price is unchanged.

What stays on the Mac

Local	Remote
editor, terminal and agent UI	model weights and inference
files before upload	prompts, approved files and tool results
tests, Git diff and permissions	model responses and reasoning
local fallback through Ollama or MLX	Meta or gateway billing

If data must not leave the Mac, Muse Spark 1.1 is not a sensible default. A local model can handle the first pass; a hosted model can receive redacted input only when its extra capability is justified.

A reproducible comparison

Compare the models with five tasks from your actual workflow:

• a change spanning several files,
• a reproducible bug with tests,
• a tool-calling task with an intentionally missing permission,
• a long document or repository question,
• a task where the model should ask questions before editing.

Record model ID, API surface, tier, prompt, context size, cost, runtime, tool permissions and manual repairs. Then run the tests and inspect the Git diff. For computer use, a plausible-looking answer is not evidence that the requested action was completed safely.

Practical choice

Muse Spark 1.1 remains a documented cloud model ID, but it is no longer Meta’s current product reference. For new Mac projects, Muse Spark 1.2 is the natural comparison; 1.1 remains useful when compatibility or a historical result must be reproduced. Neither version runs locally on Apple Silicon. Private or offline work needs a local fallback.

Sources

Footnotes

1. Meta: Muse Spark 1.1 — status, capabilities and published comparison values. ↩ ↩² ↩³

2. Meta: Muse Spark 1.2 — current product version, 1M context, coding and tool-calling positioning. ↩ ↩²

3. Meta Model API — model IDs, standard/contributor tiers and pricing. ↩ ↩²

4. Meta Research: Introducing Muse Code and Muse Spark 1.2 ↩

5. Meta Research: Muse Spark 1.2 methodology ↩

6. Meta Model API: model documentation ↩

7. Meta: Introducing Muse Spark 1.1 — original product announcement. ↩

8. Meta Model API documentation — base URL, compatible API surfaces and context window. ↩

9. Vercel AI Gateway: Muse Spark 1.1 — gateway slug, provider data and pricing. ↩