WritingmateWritingmate
Model Comparison

Ministral 8B vs Hy-MT2-30B-A3BWhich Is Better in 2026?

Mistral: Ministral 8B logoMistral AI•Tencent: Hy-MT2-30B-A3B logoTencent

Ministral 8B vs Hy-MT2-30B-A3B: which should you choose in 2026?

Ministral 8B (by Mistral AI) and Hy-MT2-30B-A3B (by Tencent) 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.

Ministral 8B is about 1.2× cheaper on a blended 3:1 input/output basis ($0.11 vs $0.12925 per 1M tokens).

Ministral 8B has the larger context window (128,000 tokens vs 8,192 tokens).

Choose Ministral 8B if…

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

Choose Hy-MT2-30B-A3B 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.

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.

Ministral 8B and Hy-MT2-30B-A3B benchmark results
BenchmarkMinistral 8BHy-MT2-30B-A3B
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

    Ministral 8B and Hy-MT2-30B-A3B model facts
    FeatureMinistral 8BHy-MT2-30B-A3B
    Context & model facts
    DeveloperMistral AITencent
    API providerMistralTencent
    Input context128,000 tokens8,192 tokens
    Maximum output—4,096 tokens
    Released——
    Added to WritingmateOct 17, 2024Aug 20, 2026
    LicenseNot availableNot available
    Knowledge cutoff2024-09-30—
    Capabilities
    InputsTextText
    OutputsTextText
    Provider endpoint accepts tool parametersNoNo
    ReasoningNoNo
    VisionNoNo
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$0.11$0.074
    Output (per 1M tokens)$0.11$0.295
    Blended 3:1 input/output$0.11$0.12925
    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 20, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing Ministral 8B from Mistral AI with Hy-MT2-30B-A3B from Tencent? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for Ministral 8B and Hy-MT2-30B-A3B
    PlanPriceMinistral 8BHy-MT2-30B-A3BAI 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
    View Plans & Pricing

    Ministral 8B vs Hy-MT2-30B-A3B FAQ

    Which is better, Ministral 8B or Hy-MT2-30B-A3B?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Ministral 8B is about 1.2× cheaper on a blended 3:1 input/output basis ($0.11 vs $0.12925 per 1M tokens). Ministral 8B has the larger context window (128,000 tokens vs 8,192 tokens).

    Which model is cheaper to use through an API?

    Ministral 8B is about 1.2× cheaper on a blended 3:1 input/output basis ($0.11 vs $0.12925 per 1M tokens).

    Which model supports more context?

    Ministral 8B has the larger context window (128,000 tokens vs 8,192 tokens).

    Can I switch between Ministral 8B and Hy-MT2-30B-A3B?

    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.