Hunyuan Hy4 vs MAI-Thinking-1

Tencent · China  |  Microsoft · US · Updated June 2026

Quick verdict

Pick Hunyuan Hy4 for first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview or tencent-reported gains over the preview of 19.1% on gamedev and 9.8% on gamelogic. Pick MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%) or microsoft's first in-house flagship reasoner, trained without openai distillation. On a tight budget at scale, MAI-Thinking-1 is the value pick.

Hunyuan Hy4 (Tencent, China) and MAI-Thinking-1 (Microsoft, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Hunyuan Hy4 is tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecHunyuan Hy4MAI-Thinking-1
ProviderTencent (China) Microsoft (US)
ReleasedNovember 4, 2026 August 12, 2026
Context window1M tokens (~1,573 pages) 256K (~384 pages)
Price (in/out)$0.9/$2.7 per 1M tokens Not published
Open weight?No — API only No — API only
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

First Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview

Hunyuan Hy4

MAI-Thinking-1 is comparatively weak here — closed and in private preview — no open weights, no published pricing, thin availability

Tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic

Hunyuan Hy4

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public — and it carries the larger 1M tokens context.

Tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97

Hunyuan Hy4

MAI-Thinking-1 is comparatively weak here — benchmarks are largely self-reported

Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)

MAI-Thinking-1

MAI-Thinking-1 lists very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%) among its strengths; Hunyuan Hy4 does not.

Microsoft's first in-house flagship reasoner, trained without OpenAI distillation

MAI-Thinking-1

MAI-Thinking-1 lists microsoft's first in-house flagship reasoner, trained without OpenAI distillation among its strengths; Hunyuan Hy4 does not.

Efficient reasoning at low token cost for its class

MAI-Thinking-1

MAI-Thinking-1 lists efficient reasoning at low token cost for its class among its strengths; Hunyuan Hy4 does not.

Lowest cost at scale

MAI-Thinking-1

Its weights are open, so at volume you pay for your own hardware instead of Hunyuan Hy4's $0.9/$2.7 per 1M tokens.

Largest single-prompt input

Hunyuan Hy4

Its 1M tokens window is about 4.1× larger than MAI-Thinking-1's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ MAI-Thinking-1

At Not published it undercuts Hunyuan Hy4, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Hunyuan Hy4

Larger 1M tokens window fits more in one prompt.

Anyone whose priority is first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview

→ Hunyuan Hy4

It is specifically built for that.

Anyone whose priority is very strong math reasoning (aime 2025 97%, aime 2026 94.5%)

→ MAI-Thinking-1

That is its strongest area.

An enterprise with regional data-residency rules

→ MAI-Thinking-1 or Hunyuan Hy4

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Hunyuan Hy4: where it fits

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. Released November 4, 2026 by Tencent, it is built for first Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview, tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic, tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97, and about $0.90/$2.70 per million tokens, with 50% off on Tencent Cloud TokenHub through December 31, 2026 (OpenRouter lists $0.417/$1.25 with that discount).

Its trade-offs are real: weights not public as of November 5, 2026 - Tencent says weights and system cards will come in the coming days, and no license is announced yet, only the earlier Hy4 Preview is downloadable today (Apache 2.0), published improvements are Tencent's own and mostly relative to the preview, with no SWE-bench Verified figure, and sources differ on list price: Tencent says about $0.90/$2.70, while OpenRouter and Vals show $0.83/$2.50. At $0.9 in / $2.7 out per million tokens, it sits in the budget price band.

MAI-Thinking-1: where it fits

Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Released August 12, 2026 by Microsoft, it is built for very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%), microsoft's first in-house flagship reasoner, trained without OpenAI distillation, efficient reasoning at low token cost for its class, and competitive with Claude Opus 4.6 on SWE-Bench Pro (vendor-reported).

Its trade-offs: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Hunyuan Hy4 (China) and MAI-Thinking-1 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. MAI-Thinking-1 is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both Hunyuan Hy4 and MAI-Thinking-1 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Hunyuan Hy4 or MAI-Thinking-1 better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Hunyuan Hy4 leans toward first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview while MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 or MAI-Thinking-1?

MAI-Thinking-1 is cheaper — $0.9/$2.7 per 1M tokens vs Not published.

Which has the bigger context window?

Hunyuan Hy4 — 1M tokens vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Hunyuan Hy4 and MAI-Thinking-1 together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4, MAI-Thinking-1 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Hunyuan Hy4 or MAI-Thinking-1?

Hunyuan Hy4 — released November 4, 2026, about 3 months after MAI-Thinking-1.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.