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 Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. On a tight budget at scale, ERNIE 5.0 is the value pick.
ERNIE 5.0 (Baidu, China) and Gemini 3.1 Pro (Google, 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. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: ERNIE 5.0 is about 3.3× cheaper on input ($0.6/$2.1 per 1M tokens vs $2/$12 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Gemini 3.1 Pro holds 8.2× more — 1M (~1,573 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: Gemini 3.1 Pro is the newer model by about 28 days (released February 19, 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
Gemini 3.1 Pro
Provider
Baidu (China)
Google (US)
Released
January 22, 2026
February 19, 2026
Context window
128K (~192 pages)
1M (~1,573 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$2/$12 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
26.3%
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; Gemini 3.1 Pro 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; Gemini 3.1 Pro does not.
Full multimodal input — text, image, audio and video in one 1M-token window: Gemini 3.1 Pro — Its 1M window holds about 8.2× more than ERNIE 5.0's 128K in a single prompt.
Long video and document analysis: Gemini 3.1 Pro — A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window — and it carries the larger 1M context.
Agentic reasoning (high ARC-AGI-2): Gemini 3.1 Pro — A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window — 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: Gemini 3.1 Pro — Its 1M 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 Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.1 Pro — Larger 1M 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 full multimodal input — text, image, audio and video in one 1m-token window: Gemini 3.1 Pro — That is its strongest area.
An enterprise with regional data-residency rules: Gemini 3.1 Pro 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.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." ERNIE 5.0 (China) and Gemini 3.1 Pro (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. ERNIE 5.0 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 Gemini 3.1 Pro 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 Gemini 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or Gemini 3.1 Pro?
ERNIE 5.0 is cheaper — $0.6/$2.1 per 1M tokens vs $2/$12 per 1M tokens, roughly 3.3× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 1M 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 Gemini 3.1 Pro together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, Gemini 3.1 Pro 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 Gemini 3.1 Pro?
Gemini 3.1 Pro — released February 19, 2026, about 28 days after ERNIE 5.0.
ERNIE 5.0 vs Gemini 3.1 Pro
Baidu · China | Google · 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 Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. On a tight budget at scale, ERNIE 5.0 is the value pick.
ERNIE 5.0 (Baidu, China) and Gemini 3.1 Pro (Google, 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. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: ERNIE 5.0 is about 3.3× cheaper on input ($0.6/$2.1 per 1M tokens vs $2/$12 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Gemini 3.1 Pro holds 8.2× more — 1M (~1,573 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: Gemini 3.1 Pro is the newer model by about 28 days (released February 19, 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
Gemini 3.1 Pro
Provider
Baidu (China)
Google (US)
Released
January 22, 2026
February 19, 2026
Context window
128K (~192 pages)
1M (~1,573 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$2/$12 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
26.3%
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; Gemini 3.1 Pro 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; Gemini 3.1 Pro does not.
Full multimodal input — text, image, audio and video in one 1M-token window
Gemini 3.1 Pro
Its 1M window holds about 8.2× more than ERNIE 5.0's 128K in a single prompt.
Long video and document analysis
Gemini 3.1 Pro
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window — and it carries the larger 1M context.
Agentic reasoning (high ARC-AGI-2)
Gemini 3.1 Pro
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window — 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
Gemini 3.1 Pro
Its 1M 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 Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.1 Pro
Larger 1M 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 full multimodal input — text, image, audio and video in one 1m-token window
→ Gemini 3.1 Pro
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemini 3.1 Pro 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.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." ERNIE 5.0 (China) and Gemini 3.1 Pro (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. ERNIE 5.0 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 Gemini 3.1 Pro 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 Gemini 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or Gemini 3.1 Pro?
ERNIE 5.0 is cheaper — $0.6/$2.1 per 1M tokens vs $2/$12 per 1M tokens, roughly 3.3× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 1M 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 Gemini 3.1 Pro together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, Gemini 3.1 Pro 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 Gemini 3.1 Pro?
Gemini 3.1 Pro — released February 19, 2026, about 28 days 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.