ERNIE 5.0 vs Hunyuan Hy4

Baidu · China  |  Tencent · China · Updated June 2026

Quick verdict

Pick ERNIE 5.0 for baidu's flagship omni-modal model — text, image and video understanding or particularly strong on chinese-language reasoning tasks. 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. On a tight budget at scale, ERNIE 5.0 is the value pick.

ERNIE 5.0 (Baidu) and Hunyuan Hy4 (Tencent) are two of the models people most often weigh against each other in 2026. ERNIE 5.0 is baidu's flagship omni-modal ERNIE model — strong Chinese-language and multimodal reasoning at low cost, though it trails the Western frontier on independent benchmarks. 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. 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

SpecERNIE 5.0Hunyuan Hy4
ProviderBaidu (China) Tencent (China)
ReleasedJanuary 22, 2026 November 4, 2026
Context window128K (~192 pages) 1M tokens (~1,573 pages)
Price (in/out)$0.6/$2.1 per 1M tokens $0.9/$2.7 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, video, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Baidu's flagship omni-modal model — text, image and video understanding

ERNIE 5.0

Baidu's flagship omni-modal ERNIE model — strong Chinese-language and multimodal reasoning at low cost, though it trails the Western frontier on independent benchmarks — and it runs cheaper at $0.6/$2.1 per 1M tokens.

Particularly strong on Chinese-language reasoning tasks

ERNIE 5.0

ERNIE 5.0 lists particularly strong on Chinese-language reasoning tasks among its strengths; Hunyuan Hy4 does not.

Competitive API pricing (around $0.60/$2.10 per million tokens)

ERNIE 5.0

ERNIE 5.0 lists competitive API pricing (around $0.60/$2.10 per million tokens) among its strengths; Hunyuan Hy4 does not.

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

Hunyuan Hy4

ERNIE 5.0 is comparatively weak here — trails the Western frontier on aggregate independent tests (AA Intelligence Index ~22 for the tracked Thinking Preview)

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

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 is the newer of the two.

Lowest cost at scale

ERNIE 5.0

At $0.6/$2.1 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Hunyuan Hy4

Its 1M tokens window is about 8.2× larger than ERNIE 5.0's 128K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ ERNIE 5.0

At $0.6/$2.1 per 1M tokens 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 baidu's flagship omni-modal model — text, image and video understanding

→ ERNIE 5.0

It is specifically built for that.

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

→ Hunyuan Hy4

That is its strongest area.

ERNIE 5.0: where it fits

Baidu's flagship omni-modal ERNIE model — strong Chinese-language and multimodal reasoning at low cost, though it trails the Western frontier on independent benchmarks. Released January 22, 2026 by Baidu, it is built for baidu's flagship omni-modal model — text, image and video understanding, particularly strong on Chinese-language reasoning tasks, competitive API pricing (around $0.60/$2.10 per million tokens), and backed by a major lab with deep China-market integration.

Its trade-offs are real: trails the Western frontier on aggregate independent tests (AA Intelligence Index ~22 for the tracked Thinking Preview), parameter and architecture details are vendor-stated and opaque, closed weights on a China-hosted API, and 128K context is smaller than 1M-token rivals. At $0.6 in / $2.1 out per million tokens, it sits in the budget price band.

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: 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.

The bottom line for this matchup

ERNIE 5.0 and Hunyuan Hy4 overlap enough that the right pick depends on your specific job. ERNIE 5.0 costs less per token; Hunyuan Hy4 holds the larger context; and each leads in its own area — ERNIE 5.0 for baidu's flagship omni-modal model — text, image and video understanding, Hunyuan Hy4 for first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both ERNIE 5.0 and Hunyuan Hy4 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 ERNIE 5.0 or Hunyuan Hy4 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, ERNIE 5.0 leans toward baidu's flagship omni-modal model — text, image and video understanding while Hunyuan Hy4 leans toward first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, ERNIE 5.0 or Hunyuan Hy4?

ERNIE 5.0 is cheaper — $0.6/$2.1 per 1M tokens vs $0.9/$2.7 per 1M tokens, roughly 1.5× apart on input.

Which has the bigger context window?

Hunyuan Hy4 — 1M tokens vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both ERNIE 5.0 and Hunyuan Hy4 together?

Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, Hunyuan Hy4 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, ERNIE 5.0 or Hunyuan Hy4?

Hunyuan Hy4 — released November 4, 2026, about 10 months after ERNIE 5.0.

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.