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Model Comparison

DeepSeek V4.1 Flash vs Mercury 3Which Is Better in 2026?

DeepSeek: DeepSeek V4.1 Flash logoDeepSeek•
Inception

DeepSeek V4.1 Flash vs Mercury 3: which should you choose in 2026?

DeepSeek V4.1 Flash (by DeepSeek) and Mercury 3 (by Inception) 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.

DeepSeek V4.1 Flash is about 5.6× cheaper on a blended 3:1 input/output basis ($0.0292 vs $0.1625 per 1M tokens).

Choose DeepSeek V4.1 Flash if…

  • • lower blended API cost matters for your workload
  • • you need image inputs

Choose Mercury 3 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.

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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.

DeepSeek V4.1 Flash and Mercury 3 benchmark results
BenchmarkDeepSeek V4.1 FlashMercury 3
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

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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

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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

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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

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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

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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

    DeepSeek V4.1 Flash and Mercury 3 model facts
    FeatureDeepSeek V4.1 FlashMercury 3
    Context & model facts
    DeveloperDeepSeekInception
    API providerDeepSeekInception
    Input context1,048,576 tokens1,000,000 tokens
    Maximum output943,718 tokens131,072 tokens
    Released——
    Added to WritingmateSep 10, 2026Oct 16, 2026
    LicenseNot availableNot available
    Knowledge cutoff——
    Capabilities
    InputsText, ImageText
    OutputsTextText
    Provider endpoint accepts tool parametersYesYes
    ReasoningYesYes
    VisionYesNo
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.0352$0.10
    Output (per 1M tokens)$0.0112$0.35
    Blended 3:1 input/output$0.0292$0.1625
    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 16, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing DeepSeek V4.1 Flash from DeepSeek with Mercury 3 from Inception? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for DeepSeek V4.1 Flash and Mercury 3
    PlanPriceDeepSeek V4.1 FlashMercury 3AI 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

    DeepSeek V4.1 Flash vs Mercury 3 FAQ

    Which is better, DeepSeek V4.1 Flash or Mercury 3?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. DeepSeek V4.1 Flash is about 5.6× cheaper on a blended 3:1 input/output basis ($0.0292 vs $0.1625 per 1M tokens).

    Which model is cheaper to use through an API?

    DeepSeek V4.1 Flash is about 5.6× cheaper on a blended 3:1 input/output basis ($0.0292 vs $0.1625 per 1M tokens).

    Which model supports more context?

    The published context windows are close enough that this page does not treat the difference as a material advantage.

    Can I switch between DeepSeek V4.1 Flash and Mercury 3?

    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.