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Model Comparison

Muse Glimmer 30B vs Nex-N2-MiniWhich Is Better in 2026?

Muse Glimmer 30B vs Nex-N2-Mini: which should you choose in 2026?

Muse Glimmer 30B (by Meta) and Nex-N2-Mini (by Nex AGI) 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.

Nex-N2-Mini is about 14.6× cheaper on a blended 3:1 input/output basis ($0.04375 vs $0.6375 per 1M tokens).

Nex-N2-Mini has the larger context window (262,144 tokens vs 131,072 tokens).

Choose Muse Glimmer 30B if…

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

Choose Nex-N2-Mini if…

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

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.

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Performance benchmarks

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

Muse Glimmer 30B and Nex-N2-Mini benchmark results
BenchmarkMuse Glimmer 30BNex-N2-Mini
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 Glimmer 30B and Nex-N2-Mini model facts
    FeatureMuse Glimmer 30BNex-N2-Mini
    Context & model facts
    DeveloperMetaNex AGI
    API providerMetaNex AGI
    Input context131,072 tokens262,144 tokens
    Maximum output262,144 tokens
    Released
    Added to WritingmateAug 9, 2026Jun 24, 2026
    LicenseNot availableNot available
    Knowledge cutoff
    Capabilities
    InputsText, ImageText, Image
    OutputsTextText
    Provider endpoint accepts tool parametersYesYes
    ReasoningYesYes
    VisionYesYes
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.35$0.025
    Output (per 1M tokens)$1.50$0.10
    Blended 3:1 input/output$0.6375$0.04375
    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 Aug 9, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing Muse Glimmer 30B from Meta with Nex-N2-Mini from Nex AGI? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for Muse Glimmer 30B and Nex-N2-Mini
    PlanPriceMuse Glimmer 30BNex-N2-MiniAI 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 Glimmer 30B vs Nex-N2-Mini FAQ

    Which is better, Muse Glimmer 30B or Nex-N2-Mini?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Nex-N2-Mini is about 14.6× cheaper on a blended 3:1 input/output basis ($0.04375 vs $0.6375 per 1M tokens). Nex-N2-Mini has the larger context window (262,144 tokens vs 131,072 tokens).

    Which model is cheaper to use through an API?

    Nex-N2-Mini is about 14.6× cheaper on a blended 3:1 input/output basis ($0.04375 vs $0.6375 per 1M tokens).

    Which model supports more context?

    Nex-N2-Mini has the larger context window (262,144 tokens vs 131,072 tokens).

    Can I switch between Muse Glimmer 30B and Nex-N2-Mini?

    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.