Hunyuan Hy4 Preview vs Llama 4 Scout

Tencent · China | Meta · US · Updated June 2026

Quick verdict

Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Pick Llama 4 Scout for largest advertised context (10m) or open weights, single-gpu friendly. On a tight budget at scale, Llama 4 Scout is the value pick.

Hunyuan Hy4 Preview (Tencent, China) and Llama 4 Scout (Meta, 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. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

▸Context window: Llama 4 Scout holds 10× more — 10M (~15,000 pages) vs 1M+ tokens (~1,500 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Hunyuan Hy4 Preview is the newer model by about 17 months (released August 28, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.

Side-by-side specs

Spec	Hunyuan Hy4 Preview	Llama 4 Scout
Provider	Tencent (China)	Meta (US)
Released	August 28, 2026	April 2025
Context window	1M+ tokens (~1,500 pages)	10M (~15,000 pages)
Price (in/out)	$0.834/$2.501 per 1M tokens	Open weight (self-host / free)
Open weight?	Yes — self-hostable	Yes — self-hostable
Modalities	text	text, image, code
SWE-Bench Verified	Not published	Not published
MRCR v2 @ 1M	Not published	15%

Who wins what

GPQA Diamond (92.3)

Hunyuan Hy4 Preview

Terminal-Bench (85.4)

Hunyuan Hy4 Preview

Hunyuan Hy4 Preview lists terminal-Bench (85.4) among its strengths; Llama 4 Scout does not.

SWE-bench Multilingual (82.9)

Hunyuan Hy4 Preview

Hunyuan Hy4 Preview lists sWE-bench Multilingual (82.9) among its strengths; Llama 4 Scout does not.

Largest advertised context (10M)

Llama 4 Scout

Its 10M window holds about 10× more than Hunyuan Hy4 Preview's 1M+ tokens in a single prompt.

Open weights, single-GPU friendly

Llama 4 Scout

The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.

Self-hosted, data-private deployment

Llama 4 Scout

Llama 4 Scout lists self-hosted, data-private deployment among its strengths; Hunyuan Hy4 Preview does not.

Lowest cost at scale

Llama 4 Scout

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.

Largest single-prompt input

Llama 4 Scout

Its 10M window is about 10× larger than Hunyuan Hy4 Preview's 1M+ tokens, fitting roughly 15,000 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Llama 4 Scout

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

Someone analysing very long documents or codebases

→ Llama 4 Scout

Larger 10M window fits more in one prompt.

Anyone whose priority is gpqa diamond (92.3)

→ Hunyuan Hy4 Preview

It is specifically built for that.

Anyone whose priority is largest advertised context (10m)

→ Llama 4 Scout

That is its strongest area.

An enterprise with regional data-residency rules

→ Llama 4 Scout 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.

Llama 4 Scout: where it fits

The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.

Its trade-offs: effective recall degrades far below 10M, and ~15% on long-context multi-needle reasoning. 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 Llama 4 Scout (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Llama 4 Scout 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 Llama 4 Scout 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 Llama 4 Scout 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 Preview leans toward gpqa diamond (92.3) while Llama 4 Scout leans toward largest advertised context (10m), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 Preview or Llama 4 Scout?

Llama 4 Scout is cheaper — $0.834/$2.501 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

Llama 4 Scout — 10M vs 1M+ tokens, about 10× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Hunyuan Hy4 Preview and Llama 4 Scout together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4 Preview, Llama 4 Scout 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 Llama 4 Scout?

Hunyuan Hy4 Preview — released August 28, 2026, about 17 months after Llama 4 Scout.

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