Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, MiMo-V2.5 is the value pick.
GLM 5 (Z.ai) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 7.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $1/$3.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: MiMo-V2.5 holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: MiMo-V2.5 is the newer model by about 2 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 5
MiMo-V2.5
Provider
Z.ai (China)
Xiaomi (China)
Released
February 11, 2026
April 22, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, audio, video, code
SWE-Bench Verified
77.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic planning and long-horizon coding workflows: GLM 5 — A core design strength of GLM 5.
Complex systems design and backend reasoning: GLM 5 — A core design strength of GLM 5.
Iterative self-correction on autonomous tasks: GLM 5 — A core design strength of GLM 5.
Native omnimodal — strong image and video understanding: MiMo-V2.5 — A core design strength of MiMo-V2.5.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — A core design strength of MiMo-V2.5.
Agent-framework integration: MiMo-V2.5 — A core design strength of MiMo-V2.5.
Lowest cost at scale: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: MiMo-V2.5 — Its 1M window is about 5× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiMo-V2.5 — Larger 1M window fits more in one prompt.
Anyone whose priority is agentic planning and long-horizon coding workflows: GLM 5 — It is specifically built for that.
Anyone whose priority is native omnimodal — strong image and video understanding: MiMo-V2.5 — That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GLM 5 and MiMo-V2.5 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiMo-V2.5 holds the larger context; and each leads in its own area — GLM 5 for agentic planning and long-horizon coding workflows, MiMo-V2.5 for native omnimodal — strong image and video understanding. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is GLM 5 or MiMo-V2.5 better for coding?
Public SWE-Bench figures are not available for MiMo-V2.5, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or MiMo-V2.5?
MiMo-V2.5 is cheaper — $1/$3.2 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 7.1× apart on input.
Which has the bigger context window?
MiMo-V2.5 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, MiMo-V2.5 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, GLM 5 or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 2 months after GLM 5.
GLM 5 vs MiMo-V2.5
Z.ai · China | Xiaomi · China · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, MiMo-V2.5 is the value pick.
GLM 5 (Z.ai) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiMo-V2.5 is about 7.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $1/$3.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: MiMo-V2.5 holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: MiMo-V2.5 is the newer model by about 2 months (released April 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 5
MiMo-V2.5
Provider
Z.ai (China)
Xiaomi (China)
Released
February 11, 2026
April 22, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, audio, video, code
SWE-Bench Verified
77.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
A core design strength of GLM 5.
Complex systems design and backend reasoning
GLM 5
A core design strength of GLM 5.
Iterative self-correction on autonomous tasks
GLM 5
A core design strength of GLM 5.
Native omnimodal — strong image and video understanding
MiMo-V2.5
A core design strength of MiMo-V2.5.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
A core design strength of MiMo-V2.5.
Agent-framework integration
MiMo-V2.5
A core design strength of MiMo-V2.5.
Lowest cost at scale
MiMo-V2.5
At $0.14/$0.28 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
MiMo-V2.5
Its 1M window is about 5× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.5
Larger 1M window fits more in one prompt.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GLM 5 and MiMo-V2.5 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiMo-V2.5 holds the larger context; and each leads in its own area — GLM 5 for agentic planning and long-horizon coding workflows, MiMo-V2.5 for native omnimodal — strong image and video understanding. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GLM 5 and MiMo-V2.5 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 MiMo-V2.5, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or MiMo-V2.5?
MiMo-V2.5 is cheaper — $1/$3.2 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 7.1× apart on input.
Which has the bigger context window?
MiMo-V2.5 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, MiMo-V2.5 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, GLM 5 or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 2 months after GLM 5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.