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Model comparison

Inkling vs Muse Spark 1.3

Compare Inkling and Muse Spark 1.3 using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.

Facts checked September 4, 2026

Estimate your cost

Set your usage. Your estimate updates as you type.

Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.

One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.

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How this estimate works

Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.

Estimate your cost
ModelEstimated total (USD)
InklingThinking Machines LabNo reviewed rate
Muse Spark 1.3MetaNo reviewed rate

Quick take

Inkling

Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows.

Best for

  • Teams that want an adaptable open-weight foundation model
  • Agentic coding and tool-use experiments
  • Private or specialized deployments with multimodal inputs

Watch out for

A 975B model is a serious serving project even with sparse activation. Compare the exact hosted or self-hosted route, and do not assume the model's 1M maximum context is available on every provider.

Muse Spark 1.3

Meta's latest multimodal reasoning model for long-running agents, coding, tools, and complex user collaboration.

Best for

  • Long-horizon coding and agent projects
  • Tool workflows that need user checkpoints
  • Multimodal work over files, images, video, and PDFs

Watch out for

Meta's public launch does not publish every operational limit or one complete API data-use commitment. Check the live model page, price, region, retention controls, and maximum output before production.

Compare the published facts

Inkling vs Muse Spark 1.3

Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.

Text & reasoningInklingMuse Spark 1.3
Context windowMaximum combined prompt and working context documented by the provider.Up to 1M tokens; Tinker offers 64K and 256K1M active context management in the Muse Spark API family
Maximum outputProvider-published response limit, where available.Not separately publishedNot separately published
Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff.Not publishedNot published
Input priceCurrent standard list price per million input tokens unless noted.Hosting dependentSee live Meta Model API price
Output priceCurrent standard list price per million output tokens unless noted.Hosting dependentSee live Meta Model API price
InputsMedia types accepted by the listed model endpoint.Text, image, audioText, image, video, PDF
Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list.Agentic coding, tools, Python-assisted vision, controllable thinkingParallel tools, coding, long-running agents, high reasoning

How to choose

Compare the job, not the hype.

Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.

Inkling

The open weights can be self-hosted so request data stays in infrastructure you control. Tinker and partner-hosted routes have separate retention and training-use terms that must be checked with the selected provider.

Muse Spark 1.3

The public Muse Spark model and release pages reviewed do not state one complete API retention or training-use commitment. Check the current Meta Model API terms and account controls before using private data.

Frequently asked questions

Inkling vs Muse Spark 1.3 FAQ

What is the main difference between Inkling and Muse Spark 1.3?

Inkling: Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows. Muse Spark 1.3: Meta's latest multimodal reasoning model for long-running agents, coding, tools, and complex user collaboration.

Should I choose Inkling or Muse Spark 1.3?

Consider Inkling when your priority is Teams that want an adaptable open-weight foundation model. Consider Muse Spark 1.3 when your priority is Long-horizon coding and agent projects. Test both with your own data and provider route before committing.

Is this Inkling vs Muse Spark 1.3 comparison based on Cody benchmarks?

No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.