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 MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. Choose MiniMax M2.7 if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and MiniMax M2.7 (MiniMax) 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. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: MiniMax M2.7 is about 2× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.6/$2.1 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: MiniMax M2.7 holds 1.6× more — 205K (~307 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: MiniMax M2.7 is the newer model by about 55 days (released March 18, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
ERNIE 5.0
MiniMax M2.7
Provider
Baidu (China)
MiniMax (China)
Released
January 22, 2026
March 18, 2026
Context window
128K (~192 pages)
205K (~307 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
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 — ERNIE 5.0 lists baidu's flagship omni-modal model — text, image and video understanding among its strengths; MiniMax M2.7 does not.
Particularly strong on Chinese-language reasoning tasks: ERNIE 5.0 — ERNIE 5.0 lists particularly strong on Chinese-language reasoning tasks among its strengths; MiniMax M2.7 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; MiniMax M2.7 does not.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported): MiniMax M2.7 — At $0.3/$1.2 per 1M tokens it undercuts ERNIE 5.0 ($0.6/$2.1 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index: MiniMax M2.7 — ERNIE 5.0 is comparatively weak here — trails the Western frontier on aggregate independent tests (AA Intelligence Index ~22 for the tracked Thinking Preview)
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware: MiniMax M2.7 — Open weights make this possible at all — ERNIE 5.0 is API-only, so it cannot leave the vendor's servers.
Lowest cost at scale: MiniMax M2.7 — At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: MiniMax M2.7 — Its 205K window is about 1.6× larger than ERNIE 5.0's 128K, fitting roughly 307 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiniMax M2.7 — At $0.3/$1.2 per 1M tokens it undercuts ERNIE 5.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiniMax M2.7 — Larger 205K window fits more in one prompt.
A team with data-privacy or self-hosting needs: MiniMax M2.7 — 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 agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported): MiniMax M2.7 — 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.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 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. MiniMax M2.7 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 MiniMax M2.7 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 MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or MiniMax M2.7?
MiniMax M2.7 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?
MiniMax M2.7 — 205K vs 128K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both ERNIE 5.0 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, MiniMax M2.7 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 MiniMax M2.7?
MiniMax M2.7 — released March 18, 2026, about 55 days after ERNIE 5.0.
ERNIE 5.0 vs MiniMax M2.7
Baidu · China | MiniMax · 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 MiniMax M2.7 for agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported) or independently ranked 14th of 97 on the artificial analysis intelligence index. Choose MiniMax M2.7 if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and MiniMax M2.7 (MiniMax) 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. MiniMax M2.7 is a cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. 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: MiniMax M2.7 is about 2× cheaper on input ($0.3/$1.2 per 1M tokens vs $0.6/$2.1 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: MiniMax M2.7 holds 1.6× more — 205K (~307 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: MiniMax M2.7 is the newer model by about 55 days (released March 18, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
ERNIE 5.0
MiniMax M2.7
Provider
Baidu (China)
MiniMax (China)
Released
January 22, 2026
March 18, 2026
Context window
128K (~192 pages)
205K (~307 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$0.3/$1.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
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
ERNIE 5.0 lists baidu's flagship omni-modal model — text, image and video understanding among its strengths; MiniMax M2.7 does not.
Particularly strong on Chinese-language reasoning tasks
ERNIE 5.0
ERNIE 5.0 lists particularly strong on Chinese-language reasoning tasks among its strengths; MiniMax M2.7 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; MiniMax M2.7 does not.
Agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported)
MiniMax M2.7
At $0.3/$1.2 per 1M tokens it undercuts ERNIE 5.0 ($0.6/$2.1 per 1M tokens), and that gap compounds at volume.
Independently ranked 14th of 97 on the Artificial Analysis Intelligence Index
MiniMax M2.7
ERNIE 5.0 is comparatively weak here — trails the Western frontier on aggregate independent tests (AA Intelligence Index ~22 for the tracked Thinking Preview)
Sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware
MiniMax M2.7
Open weights make this possible at all — ERNIE 5.0 is API-only, so it cannot leave the vendor's servers.
Lowest cost at scale
MiniMax M2.7
At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
MiniMax M2.7
Its 205K window is about 1.6× larger than ERNIE 5.0's 128K, fitting roughly 307 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiniMax M2.7
At $0.3/$1.2 per 1M tokens it undercuts ERNIE 5.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiniMax M2.7
Larger 205K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ MiniMax M2.7
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 agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported)
→ MiniMax M2.7
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.
MiniMax M2.7: where it fits
A cheap open-weight agentic coder with near-frontier terminal scores — held back by a non-commercial licence and non-standard benchmarks. Released March 18, 2026 by MiniMax, it is built for agentic and terminal coding well above its price tier (57.0 on Terminal-Bench 2, vendor-reported), independently ranked 14th of 97 on the Artificial Analysis Intelligence Index, sparse mixture-of-experts — roughly 230B total but only ~10B active, so it runs on local hardware, and served by five separate hosts at uniform pricing, so there is no provider lock-in.
Its trade-offs: open weights but a NON-COMMERCIAL licence — commercial use requires prior written authorisation from MiniMax, and at least one major tracker still mislabels it as MIT, reports SWE-Bench Pro instead of the standard Verified set, which blocks like-for-like comparison, and already superseded internally by M3, and its 205K context is small against 1M-class rivals. At $0.3 in / $1.2 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. MiniMax M2.7 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 MiniMax M2.7 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 MiniMax M2.7 leans toward agentic and terminal coding well above its price tier (57.0 on terminal-bench 2, vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or MiniMax M2.7?
MiniMax M2.7 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?
MiniMax M2.7 — 205K vs 128K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both ERNIE 5.0 and MiniMax M2.7 together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, MiniMax M2.7 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 MiniMax M2.7?
MiniMax M2.7 — released March 18, 2026, about 55 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.