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 MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. On a tight budget at scale, MAI-1-preview is the value pick.
ERNIE 5.0 (Baidu, China) and MAI-1-preview (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. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: both advertise 128K (~192 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: ERNIE 5.0 is the newer model by about 5 months (released January 22, 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.
Specifications
Spec
ERNIE 5.0
MAI-1-preview
Provider
Baidu (China)
Microsoft (US)
Released
January 22, 2026
August 28, 2025
Context window
128K (~192 pages)
128K (~192 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
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 — MAI-1-preview is comparatively weak here — a 'preview' release, not yet positioned as Microsoft's primary Copilot model
Particularly strong on Chinese-language reasoning tasks: ERNIE 5.0 — MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Competitive API pricing (around $0.60/$2.10 per million tokens): ERNIE 5.0 — MAI-1-preview is comparatively weak here — no public per-token API pricing - not sold as a standalone product
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI: MAI-1-preview — MAI-1-preview lists microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI among its strengths; ERNIE 5.0 does not.
Ranked in the top 15 on LM Arena at launch: MAI-1-preview — MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; ERNIE 5.0 does not.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment: MAI-1-preview — MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; ERNIE 5.0 does not.
Lowest cost at scale: MAI-1-preview — Its weights are open, so at volume you pay for your own hardware instead of ERNIE 5.0's $0.6/$2.1 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-1-preview — At Not published it undercuts ERNIE 5.0, and on millions of tokens that margin decides the monthly bill.
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 microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai: MAI-1-preview — That is its strongest area.
An enterprise with regional data-residency rules: MAI-1-preview or ERNIE 5.0 — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." ERNIE 5.0 (China) and MAI-1-preview (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. MAI-1-preview 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.
Frequently asked questions
Is ERNIE 5.0 or MAI-1-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 MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or MAI-1-preview?
MAI-1-preview is cheaper — $0.6/$2.1 per 1M tokens vs Not published.
Which has the bigger context window?
Both advertise 128K (~192 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both ERNIE 5.0 and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, MAI-1-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 MAI-1-preview?
ERNIE 5.0 — released January 22, 2026, about 5 months after MAI-1-preview.
ERNIE 5.0 vs MAI-1-preview
Baidu · China | Microsoft · US · 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 MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. On a tight budget at scale, MAI-1-preview is the value pick.
ERNIE 5.0 (Baidu, China) and MAI-1-preview (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. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: both advertise 128K (~192 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: ERNIE 5.0 is the newer model by about 5 months (released January 22, 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
ERNIE 5.0
MAI-1-preview
Provider
Baidu (China)
Microsoft (US)
Released
January 22, 2026
August 28, 2025
Context window
128K (~192 pages)
128K (~192 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
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
MAI-1-preview is comparatively weak here — a 'preview' release, not yet positioned as Microsoft's primary Copilot model
Particularly strong on Chinese-language reasoning tasks
ERNIE 5.0
MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Competitive API pricing (around $0.60/$2.10 per million tokens)
ERNIE 5.0
MAI-1-preview is comparatively weak here — no public per-token API pricing - not sold as a standalone product
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI
MAI-1-preview
MAI-1-preview lists microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI among its strengths; ERNIE 5.0 does not.
Ranked in the top 15 on LM Arena at launch
MAI-1-preview
MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; ERNIE 5.0 does not.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment
MAI-1-preview
MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; ERNIE 5.0 does not.
Lowest cost at scale
MAI-1-preview
Its weights are open, so at volume you pay for your own hardware instead of ERNIE 5.0's $0.6/$2.1 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-1-preview
At Not published it undercuts ERNIE 5.0, and on millions of tokens that margin decides the monthly bill.
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 microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai
→ MAI-1-preview
That is its strongest area.
An enterprise with regional data-residency rules
→ MAI-1-preview or ERNIE 5.0
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." ERNIE 5.0 (China) and MAI-1-preview (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. MAI-1-preview 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 ERNIE 5.0 and MAI-1-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.
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 MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or MAI-1-preview?
MAI-1-preview is cheaper — $0.6/$2.1 per 1M tokens vs Not published.
Which has the bigger context window?
Both advertise 128K (~192 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both ERNIE 5.0 and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, MAI-1-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 MAI-1-preview?
ERNIE 5.0 — released January 22, 2026, about 5 months after MAI-1-preview.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.