Muse Spark 1.2 Limits
Rate limits, context window, quotas, and modality — what Meta has published and what to verify at the vendor page.
Muse Spark 1.2 limits were not published in full at Meta's 2026-08-05 launch. This page states what Meta confirmed, what is still unknown, and where to verify.
The rule for this page is strict: nothing is invented. If Meta has not published a number, you will see the phrase "not published — verify at https://developer.meta.com/ai/products/muse-code/" and a suggestion for what to check.
Use this as a pre-integration checklist before wiring Muse Spark 1.2 into a production system.
Rate Limits (RPM / TPM)
Meta has not published requests-per-minute or tokens-per-minute limits for Muse Spark 1.2 at launch. Verify at https://developer.meta.com/ai/products/muse-code/.
For any production workload — batch scoring, high-QPS agent loops, or CI-integrated code review — you should confirm both per-key and per-org limits directly before capacity planning.
Muse Code inherits these limits since it uses Muse Spark 1.2 as its backing model. Multi-agent runs can burn through rate quotas faster than single-turn chat because workers and reviewers issue requests in parallel.
- RPM: not published — verify at vendor page
- TPM: not published — verify at vendor page
- Multi-agent workloads amplify rate consumption
- Confirm per-key AND per-org limits
Context Window and Output Cap
Muse Spark 1.2 context window and output-token cap were not published at launch — verify at https://developer.meta.com/ai/products/muse-code/.
Muse Spark 1.1 shipped with a 1M-token context window. Whether 1.2 preserves that, expands it, or trades depth for cost is not documented in the launch materials.
For long-horizon coding sessions (large repos, long test outputs, replay of full event logs), a 200k+ window is the practical floor. Confirm before you architect a repo-wide agent.
- Context window: not published — verify at vendor page
- Output-token cap: not published
- 1.1 baseline was 1M tokens (unconfirmed for 1.2)
- Repo-wide agents need 200k+ minimum
Modality and Built-In Tools
Muse Spark 1.2 is positioned as coding-grade, but Meta has not documented vision, audio, or structured-data modality beyond text and code — verify at https://developer.meta.com/ai/products/muse-code/.
Muse Code's exact list of built-in tools was not published beyond the "file edit, tool call" bucket. Whether it includes shell exec, web fetch, git ops, or MCP support is not documented in the launch materials.
Fine-tuning availability for Muse Spark 1.2 is also unpublished. Teams that rely on domain fine-tunes should not assume parity with prior Meta open-weights releases. The exception is Muse Spark Open, the open-weights version Meta released on October 15, 2026. Its Muse Model License allows fine-tuning and distillation, but it is a separate 816B-parameter download, not the hosted 1.2 model.
- Vision / audio / structured-data: not published
- Full built-in tools list: not published
- Fine-tuning: not published
- Do not assume open-weights parity
Compliance, SLA, and Data Residency
Meta has not published enterprise SLA, SOC 2, HIPAA, or data-residency status for Muse Spark 1.2 at launch. Verify at https://developer.meta.com/ai/products/muse-code/.
The Contributor tier explicitly permits Meta to use prompts and outputs to improve their products. Regulated teams should default to Standard until Meta publishes formal certifications.
In our engagement with HOA and condo boards we treat every new model as SOC-2-absent until the vendor page shows an actual attestation. Muse Spark 1.2 is at that stage today.
- SLA: not published
- SOC 2 / HIPAA: not published
- Data residency: not published
- Regulated teams default to Standard, not Contributor
How to Use Muse Spark 1.2
To use Muse Spark 1.2 effectively, start by choosing an interface that exposes the exact model you need for your workload. Test a new configuration on a single representative task, such as drafting a routine email or parsing a short document, before expanding to full automation. Inspect the saved output directly to confirm formatting, accuracy, and adherence to your prompt instructions.
For coding tasks, Cursor serves as an editor option when the target model appears on its supported list. Check current model availability before setup to confirm the exact model is listed. Once connected, save your prompts and review the generated diffs locally before applying changes to your main codebase.
Frequently Asked Questions
- Meta has not published RPM or TPM limits at launch. Verify at https://developer.meta.com/ai/products/muse-code/.
- Meta has not published the context window at launch. Muse Spark 1.1 shipped with 1M tokens — verify at https://developer.meta.com/ai/products/muse-code/.
- Meta has not documented vision or audio modality at launch. Confirm at the vendor page.
- Meta has not published SOC 2 or HIPAA attestations at launch. Regulated teams should default to Standard tier and confirm certifications before use.
- Fine-tuning availability for the hosted Muse Spark 1.2 model is not documented. Do not assume parity with prior Meta open-weights releases. If you need weights you can fine-tune, Meta released Muse Spark Open on October 15, 2026 under the Muse Model License, which allows it.
- The full built-in tool list was not published beyond "file edit, tool call". Verify at https://developer.meta.com/ai/products/muse-code/.
Sizing Muse Spark 1.2 for a Production Workload?
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