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 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Choose Hunyuan Hy4 Preview if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and Hunyuan Hy4 Preview (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 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: ERNIE 5.0 is about 1.4× cheaper on input ($0.6/$2.1 per 1M tokens vs $0.834/$2.501 per 1M tokens) — modest, but it adds up at steady volume.
Context window: Hunyuan Hy4 Preview holds 7.8× more — 1M+ tokens (~1,500 pages) vs 128K (~192 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 7 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
ERNIE 5.0
Hunyuan Hy4 Preview
Provider
Baidu (China)
Tencent (China)
Released
January 22, 2026
August 28, 2026
Context window
128K (~192 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Baidu's flagship omni-modal model — text, image and video understanding: ERNIE 5.0 — Hunyuan Hy4 Preview is comparatively weak here — labeled a 'preview', not yet Tencent's finalized GA flagship
Particularly strong on Chinese-language reasoning tasks: 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.
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 Preview does not.
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 carries the larger 1M+ tokens context.
Terminal-Bench (85.4): 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 its weights are open while ERNIE 5.0 is API-only.
SWE-bench Multilingual (82.9): 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.
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 Preview — Its 1M+ tokens window is about 7.8× larger than ERNIE 5.0's 128K, fitting roughly 1,500 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 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Hunyuan Hy4 Preview — Larger 1M+ tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: Hunyuan Hy4 Preview — Open weights let you run it on your own hardware; ERNIE 5.0 is API-only.
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 gpqa diamond (92.3): Hunyuan Hy4 Preview — 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 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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. Hunyuan Hy4 Preview gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. ERNIE 5.0 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is ERNIE 5.0 or Hunyuan Hy4 Preview 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 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while ERNIE 5.0 is API-metered at $0.6/$2.1 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 128K, about 7.8× 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 Preview together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, Hunyuan Hy4 Preview 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 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 7 months after ERNIE 5.0.
ERNIE 5.0 vs Hunyuan Hy4 Preview
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 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Choose Hunyuan Hy4 Preview if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and Hunyuan Hy4 Preview (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 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: ERNIE 5.0 is about 1.4× cheaper on input ($0.6/$2.1 per 1M tokens vs $0.834/$2.501 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: Hunyuan Hy4 Preview holds 7.8× more — 1M+ tokens (~1,500 pages) vs 128K (~192 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 7 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
ERNIE 5.0
Hunyuan Hy4 Preview
Provider
Baidu (China)
Tencent (China)
Released
January 22, 2026
August 28, 2026
Context window
128K (~192 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Baidu's flagship omni-modal model — text, image and video understanding
ERNIE 5.0
Hunyuan Hy4 Preview is comparatively weak here — labeled a 'preview', not yet Tencent's finalized GA flagship
Particularly strong on Chinese-language reasoning tasks
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.
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 Preview does not.
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 carries the larger 1M+ tokens context.
Terminal-Bench (85.4)
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 its weights are open while ERNIE 5.0 is API-only.
SWE-bench Multilingual (82.9)
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.
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 Preview
Its 1M+ tokens window is about 7.8× larger than ERNIE 5.0's 128K, fitting roughly 1,500 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 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Hunyuan Hy4 Preview
Larger 1M+ tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Hunyuan Hy4 Preview
Open weights let you run it on your own hardware; ERNIE 5.0 is API-only.
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 gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
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 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: 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.
The bottom line for this matchup
The defining split here is open vs. closed. Hunyuan Hy4 Preview gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. ERNIE 5.0 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both ERNIE 5.0 and Hunyuan Hy4 Preview 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.
Is ERNIE 5.0 or Hunyuan Hy4 Preview 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 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while ERNIE 5.0 is API-metered at $0.6/$2.1 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 128K, about 7.8× 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 Preview together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, Hunyuan Hy4 Preview 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 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 7 months after ERNIE 5.0.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.