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Model Comparison

Seed 2.1 Turbo vs GLM 5.3 FlashWhich Is Better in 2026?

Seed 2.1 Turbo vs GLM 5.3 Flash: which should you choose in 2026?

Seed 2.1 Turbo (by ByteDance) and GLM 5.3 Flash (by Z.AI) 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.

GLM 5.3 Flash is about 8.4× cheaper on a blended 3:1 input/output basis ($0.11875 vs $1.00 per 1M tokens).

GLM 5.3 Flash has the larger context window (1,310,720 tokens vs 262,144 tokens).

Choose Seed 2.1 Turbo if…

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

Choose GLM 5.3 Flash 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.

Seed 2.1 Turbo and GLM 5.3 Flash benchmark results
BenchmarkSeed 2.1 TurboGLM 5.3 Flash
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

    Seed 2.1 Turbo and GLM 5.3 Flash model facts
    FeatureSeed 2.1 TurboGLM 5.3 Flash
    Context & model facts
    DeveloperByteDanceZ.AI
    API providerByteDance SeedZ.ai
    Input context262,144 tokens1,310,720 tokens
    Maximum output235,929 tokens131,072 tokens
    Released
    Added to WritingmateAug 12, 2026Aug 26, 2026
    LicenseNot availableNot available
    Knowledge cutoff
    Capabilities
    InputsText, Image, VideoText, Image, Video
    OutputsTextText
    Provider endpoint accepts tool parametersYesYes
    ReasoningYesYes
    VisionYesYes
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.50$0.075
    Output (per 1M tokens)$2.50$0.25
    Blended 3:1 input/output$1.00$0.11875
    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 26, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing Seed 2.1 Turbo from ByteDance with GLM 5.3 Flash from Z.AI? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for Seed 2.1 Turbo and GLM 5.3 Flash
    PlanPriceSeed 2.1 TurboGLM 5.3 FlashAI 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

    Seed 2.1 Turbo vs GLM 5.3 Flash FAQ

    Which is better, Seed 2.1 Turbo or GLM 5.3 Flash?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. GLM 5.3 Flash is about 8.4× cheaper on a blended 3:1 input/output basis ($0.11875 vs $1.00 per 1M tokens). GLM 5.3 Flash has the larger context window (1,310,720 tokens vs 262,144 tokens).

    Which model is cheaper to use through an API?

    GLM 5.3 Flash is about 8.4× cheaper on a blended 3:1 input/output basis ($0.11875 vs $1.00 per 1M tokens).

    Which model supports more context?

    GLM 5.3 Flash has the larger context window (1,310,720 tokens vs 262,144 tokens).

    Can I switch between Seed 2.1 Turbo and GLM 5.3 Flash?

    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.