WritingmateWritingmate
Model Comparison

Ling 3.1 Flash vs Sonar Pro SearchWhich Is Better in 2026?

inclusionAI•Perplexity: Sonar Pro Search logoPerplexity

Ling 3.1 Flash vs Sonar Pro Search: which should you choose in 2026?

Ling 3.1 Flash (by inclusionAI) and Sonar Pro Search (by Perplexity) 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.

Ling 3.1 Flash has no token charge in the catalog; the other model costs $6.00 per 1M tokens on a blended 3:1 input/output basis.

Ling 3.1 Flash has the larger context window (262,144 tokens vs 200,000 tokens).

Choose Ling 3.1 Flash if…

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

Choose Sonar Pro Search if…

  • • you need image inputs

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.

Chat with both models
vs

Performance benchmarks

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

Ling 3.1 Flash and Sonar Pro Search benchmark results
BenchmarkLing 3.1 FlashSonar Pro Search
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

    Ling 3.1 Flash and Sonar Pro Search model facts
    FeatureLing 3.1 FlashSonar Pro Search
    Context & model facts
    DeveloperinclusionAIPerplexity
    API providerinclusionAIPerplexity
    Input context262,144 tokens200,000 tokens
    Maximum output32,768 tokens8,000 tokens
    Released——
    Added to WritingmateOct 2, 2026Oct 30, 2025
    LicenseNot availableNot available
    Knowledge cutoff——
    Capabilities
    InputsTextText, Image
    OutputsTextText
    Provider endpoint accepts tool parametersYesNo
    ReasoningYesYes
    VisionNoYes
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.00$3.00
    Output (per 1M tokens)$0.00$15.00
    Blended 3:1 input/output$0.00$6.00
    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 Oct 2, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing Ling 3.1 Flash from inclusionAI with Sonar Pro Search from Perplexity? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for Ling 3.1 Flash and Sonar Pro Search
    PlanPriceLing 3.1 FlashSonar Pro SearchAI ImagesAI Video
    Writingmate Pro
    Most popular
    		$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreVEO 3.1, Kling 3.0
    Writingmate Ultimate
    Power users
    		$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreVEO 3.1, Kling 3.0
    View Plans & Pricing

    Ling 3.1 Flash vs Sonar Pro Search FAQ

    Which is better, Ling 3.1 Flash or Sonar Pro Search?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Ling 3.1 Flash has no token charge in the catalog; the other model costs $6.00 per 1M tokens on a blended 3:1 input/output basis. Ling 3.1 Flash has the larger context window (262,144 tokens vs 200,000 tokens).

    Which model is cheaper to use through an API?

    Ling 3.1 Flash has no token charge in the catalog; the other model costs $6.00 per 1M tokens on a blended 3:1 input/output basis.

    Which model supports more context?

    Ling 3.1 Flash has the larger context window (262,144 tokens vs 200,000 tokens).

    Can I switch between Ling 3.1 Flash and Sonar Pro Search?

    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.