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 GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and GLM 5.1 (Z.ai) 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. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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 2.3× cheaper on input ($0.6/$2.1 per 1M tokens vs $1.4/$4.4 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GLM 5.1 holds 1.6× more — 200K (~300 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: GLM 5.1 is the newer model by about 3 months (released April 7, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
ERNIE 5.0
GLM 5.1
Provider
Baidu (China)
Z.ai (China)
Released
January 22, 2026
April 7, 2026
Context window
128K (~192 pages)
200K (~300 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$1.4/$4.4 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 — GLM 5.1 is comparatively weak here — text-only, with no image, audio, or video input
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; GLM 5.1 does not.
Long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — Its 200K window holds about 1.6× more than ERNIE 5.0's 128K in a single prompt.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch): GLM 5.1 — Open weights make this possible at all — ERNIE 5.0 is API-only, so it cannot leave the vendor's servers.
Sustained tool use across thousands of calls: GLM 5.1 — An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and it carries the larger 200K context.
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: GLM 5.1 — Its 200K window is about 1.6× larger than ERNIE 5.0's 128K, fitting roughly 300 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 GLM 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GLM 5.1 — Larger 200K window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 5.1 — 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 long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — 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.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5.1 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 GLM 5.1 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 GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or GLM 5.1?
GLM 5.1 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?
GLM 5.1 — 200K 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 GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, GLM 5.1 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 GLM 5.1?
GLM 5.1 — released April 7, 2026, about 3 months after ERNIE 5.0.
ERNIE 5.0 vs GLM 5.1
Baidu · China | Z.ai · 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 GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; ERNIE 5.0 if you want a managed API.
ERNIE 5.0 (Baidu) and GLM 5.1 (Z.ai) 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. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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 2.3× cheaper on input ($0.6/$2.1 per 1M tokens vs $1.4/$4.4 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GLM 5.1 holds 1.6× more — 200K (~300 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: GLM 5.1 is the newer model by about 3 months (released April 7, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
ERNIE 5.0
GLM 5.1
Provider
Baidu (China)
Z.ai (China)
Released
January 22, 2026
April 7, 2026
Context window
128K (~192 pages)
200K (~300 pages)
Price (in/out)
$0.6/$2.1 per 1M tokens
$1.4/$4.4 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
GLM 5.1 is comparatively weak here — text-only, with no image, audio, or video input
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; GLM 5.1 does not.
Long-horizon autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
Its 200K window holds about 1.6× more than ERNIE 5.0's 128K in a single prompt.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
Open weights make this possible at all — ERNIE 5.0 is API-only, so it cannot leave the vendor's servers.
Sustained tool use across thousands of calls
GLM 5.1
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and it carries the larger 200K context.
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
GLM 5.1
Its 200K window is about 1.6× larger than ERNIE 5.0's 128K, fitting roughly 300 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 GLM 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GLM 5.1
Larger 200K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5.1
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 long-horizon autonomous agentic engineering (up to 8-hour runs)
→ GLM 5.1
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.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5.1 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 GLM 5.1 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 GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, ERNIE 5.0 or GLM 5.1?
GLM 5.1 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?
GLM 5.1 — 200K 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 GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you ERNIE 5.0, GLM 5.1 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 GLM 5.1?
GLM 5.1 — released April 7, 2026, about 3 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.