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Model Comparison

Muse Spark 1.3 Contributor vs Ternary Bonsai 2 27BWhich Is Better in 2026?

Muse Spark 1.3 Contributor vs Ternary Bonsai 2 27B: which should you choose in 2026?

Muse Spark 1.3 Contributor (by Meta) and Ternary Bonsai 2 27B (by Prism ml) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Muse Spark 1.3 Contributor is about 1.4× cheaper on a blended 3:1 input/output basis ($0.125 vs $0.18125 per 1M tokens).

Muse Spark 1.3 Contributor has the larger context window (1,048,576 tokens vs 262,144 tokens).

Choose Muse Spark 1.3 Contributor if…

  • lower blended API cost matters for your workload
  • you work with longer documents, transcripts, or codebases

Choose Ternary Bonsai 2 27B if…

  • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

vs

Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Muse Spark 1.3 Contributor and Ternary Bonsai 2 27B benchmark results
BenchmarkMuse Spark 1.3 ContributorTernary Bonsai 2 27B
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

Benchmark sources

    Reviewed evidence last updated 2026-08-09.

    Pricing, capabilities, and model facts

    Muse Spark 1.3 Contributor and Ternary Bonsai 2 27B model facts
    FeatureMuse Spark 1.3 ContributorTernary Bonsai 2 27B
    Context & model facts
    DeveloperMetaPrism ml
    API providerMetaPrismML
    Input context1,048,576 tokens262,144 tokens
    Maximum output943,718 tokens32,768 tokens
    Released
    Added to WritingmateSep 2, 2026Sep 18, 2026
    LicenseNot availableNot available
    Knowledge cutoff
    Capabilities
    InputsText, Image, Video, File, AudioText, Image
    OutputsTextText
    Provider endpoint accepts tool parametersYesYes
    ReasoningYesYes
    VisionYesYes
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.10$0.075
    Output (per 1M tokens)$0.20$0.50
    Blended 3:1 input/output$0.125$0.18125
    API performance
    p95 latencyNot measuredNot measured
    Output throughputNot measuredNot measured
    Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

    Data sources

    • Writingmate model catalog (pricing, limits, and availability)

    Catalog data last updated Sep 18, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing Muse Spark 1.3 Contributor from Meta with Ternary Bonsai 2 27B from Prism ml? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for Muse Spark 1.3 Contributor and Ternary Bonsai 2 27B
    PlanPriceMuse Spark 1.3 ContributorTernary Bonsai 2 27BAI ImagesAI Video
    Writingmate Pro
    Most popular
    $20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
    Writingmate Ultimate
    Power users
    $60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1

    Muse Spark 1.3 Contributor vs Ternary Bonsai 2 27B FAQ

    Which is better, Muse Spark 1.3 Contributor or Ternary Bonsai 2 27B?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Muse Spark 1.3 Contributor is about 1.4× cheaper on a blended 3:1 input/output basis ($0.125 vs $0.18125 per 1M tokens). Muse Spark 1.3 Contributor has the larger context window (1,048,576 tokens vs 262,144 tokens).

    Which model is cheaper to use through an API?

    Muse Spark 1.3 Contributor is about 1.4× cheaper on a blended 3:1 input/output basis ($0.125 vs $0.18125 per 1M tokens).

    Which model supports more context?

    Muse Spark 1.3 Contributor has the larger context window (1,048,576 tokens vs 262,144 tokens).

    Can I switch between Muse Spark 1.3 Contributor and Ternary Bonsai 2 27B?

    Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.