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Model Comparison

MiniMax M2 vs Hy-MT2-7BWhich Is Better in 2026?

MiniMax: MiniMax M2 logoMiniMax•Tencent: Hy-MT2-7B logoTencent

MiniMax M2 vs Hy-MT2-7B: which should you choose in 2026?

MiniMax M2 (by MiniMax) and Hy-MT2-7B (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.

Hy-MT2-7B is about 3.5× cheaper on a blended 3:1 input/output basis ($0.12925 vs $0.44625 per 1M tokens).

MiniMax M2 has the larger context window (204,800 tokens vs 8,192 tokens).

Choose MiniMax M2 if…

  • • you work with longer documents, transcripts, or codebases
  • • you need a model with explicit reasoning support

Choose Hy-MT2-7B if…

  • • lower blended API cost matters for your workload

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.

MiniMax M2 and Hy-MT2-7B benchmark results
BenchmarkMiniMax M2Hy-MT2-7B
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

61.0%
SWE-bench
—
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

——
Arena preference scores
Arena (Text)

Human preference score

1346 ±8
—
Arena (Code/WebDev)

Human preference score for code and web development

1297 ±11
—

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Aug 23, 2026.

Pricing, capabilities, and model facts

MiniMax M2 and Hy-MT2-7B model facts
FeatureMiniMax M2Hy-MT2-7B
Context & model facts
DeveloperMiniMaxTencent
API providerMiniMaxTencent
Input context204,800 tokens8,192 tokens
Maximum output131,072 tokens4,096 tokens
Released——
Added to WritingmateOct 23, 2025Aug 19, 2026
LicenseNot availableNot available
Knowledge cutoff——
Capabilities
InputsTextText
OutputsTextText
Provider endpoint accepts tool parametersYesNo
ReasoningYesNo
VisionNoNo
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.255$0.074
Output (per 1M tokens)$1.02$0.295
Blended 3:1 input/output$0.44625$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 19, 2026.

Why Pay for Multiple Subscriptions?

Comparing MiniMax M2 from MiniMax with Hy-MT2-7B from Tencent? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for MiniMax M2 and Hy-MT2-7B
PlanPriceMiniMax M2Hy-MT2-7BAI 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

MiniMax M2 vs Hy-MT2-7B FAQ

Which is better, MiniMax M2 or Hy-MT2-7B?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Hy-MT2-7B is about 3.5× cheaper on a blended 3:1 input/output basis ($0.12925 vs $0.44625 per 1M tokens). MiniMax M2 has the larger context window (204,800 tokens vs 8,192 tokens).

Which model is cheaper to use through an API?

Hy-MT2-7B is about 3.5× cheaper on a blended 3:1 input/output basis ($0.12925 vs $0.44625 per 1M tokens).

Which model supports more context?

MiniMax M2 has the larger context window (204,800 tokens vs 8,192 tokens).

Can I switch between MiniMax M2 and Hy-MT2-7B?

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.