Hunyuan Hy4 Preview vs NVIDIA Nemotron 3 Super

Tencent · China  |  NVIDIA · US · Updated June 2026

Quick verdict

Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). On a tight budget at scale, NVIDIA Nemotron 3 Super is the value pick.

Hunyuan Hy4 Preview (Tencent, China) and NVIDIA Nemotron 3 Super (NVIDIA, 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 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.

Key differences at a glance

Side-by-side specs

SpecHunyuan Hy4 PreviewNVIDIA Nemotron 3 Super
ProviderTencent (China) NVIDIA (US)
ReleasedAugust 28, 2026 March 11, 2026
Context window1M+ tokens (~1,500 pages) 1M (~1,500 pages)
Price (in/out)$0.834/$2.501 per 1M tokens Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext text, code
SWE-Bench VerifiedNot published 60.47%
MRCR v2 @ 1MNot published Not published

Who wins what

GPQA Diamond (92.3)

Hunyuan Hy4 Preview

Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it is the newer of the two.

Terminal-Bench (85.4)

Hunyuan Hy4 Preview

Hunyuan Hy4 Preview lists terminal-Bench (85.4) among its strengths; NVIDIA Nemotron 3 Super does not.

SWE-bench Multilingual (82.9)

Hunyuan Hy4 Preview

Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) among its strengths; NVIDIA Nemotron 3 Super does not.

High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)

NVIDIA Nemotron 3 Super

NVIDIA Nemotron 3 Super lists high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B) among its strengths; Hunyuan Hy4 Preview does not.

1M-token context with strong long-context retrieval (91.6% RULER @ 1M)

NVIDIA Nemotron 3 Super

NVIDIA Nemotron 3 Super lists 1M-token context with strong long-context retrieval (91.6% RULER @ 1M) among its strengths; Hunyuan Hy4 Preview does not.

Strong math reasoning (90.21% AIME 2025)

NVIDIA Nemotron 3 Super

NVIDIA Nemotron 3 Super lists strong math reasoning (90.21% AIME 2025) among its strengths; Hunyuan Hy4 Preview does not.

Lowest cost at scale

NVIDIA Nemotron 3 Super

Its weights are open, so at volume you pay for your own hardware instead of Hunyuan Hy4 Preview's $0.834/$2.501 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

→ NVIDIA Nemotron 3 Super

At Open weight (self-host / free) it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.

Anyone whose priority is gpqa diamond (92.3)

→ Hunyuan Hy4 Preview

It is specifically built for that.

Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b)

→ NVIDIA Nemotron 3 Super

That is its strongest area.

An enterprise with regional data-residency rules

→ NVIDIA Nemotron 3 Super or Hunyuan Hy4 Preview

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

Hunyuan Hy4 Preview: where it fits

Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).

Its trade-offs are real: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.

NVIDIA Nemotron 3 Super: where it fits

NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.

Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Hunyuan Hy4 Preview (China) and NVIDIA Nemotron 3 Super (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. NVIDIA Nemotron 3 Super 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 Preview and NVIDIA Nemotron 3 Super 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 Preview or NVIDIA Nemotron 3 Super better for coding?

Public SWE-Bench figures are not available for Hunyuan Hy4 Preview, so the honest test is your own repository — run an identical real bug through both. By design, Hunyuan Hy4 Preview leans toward gpqa diamond (92.3) while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 Preview or NVIDIA Nemotron 3 Super?

NVIDIA Nemotron 3 Super is cheaper — $0.834/$2.501 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

Both advertise 1M+ tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Hunyuan Hy4 Preview and NVIDIA Nemotron 3 Super together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, NVIDIA Nemotron 3 Super 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 Preview or NVIDIA Nemotron 3 Super?

Hunyuan Hy4 Preview — released August 28, 2026, about 6 months after NVIDIA Nemotron 3 Super.

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.