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). 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 5.1 (Z.ai) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. 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. 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 10× cheaper on input ($0.14/$0.28 per 1M tokens vs $1.4/$4.4 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 15 days (released April 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 5.1
MiMo-V2.5
Provider
Z.ai (China)
Xiaomi (China)
Released
April 7, 2026
April 22, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch): GLM 5.1 — A core design strength of GLM 5.1.
Sustained tool use across thousands of calls: GLM 5.1 — A core design strength of GLM 5.1.
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 5.1, 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 long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — 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 5.1: 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 are real: 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.
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 5.1 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 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs), 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 5.1 or MiMo-V2.5 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, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) 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 5.1 or MiMo-V2.5?
MiMo-V2.5 is cheaper — $1.4/$4.4 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 10× 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 5.1 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.1, 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 5.1 or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 15 days after GLM 5.1.
GLM 5.1 vs MiMo-V2.5
Z.ai · China | Xiaomi · China · Updated June 2026
Quick verdict
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). 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 5.1 (Z.ai) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. 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. 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 10× cheaper on input ($0.14/$0.28 per 1M tokens vs $1.4/$4.4 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 15 days (released April 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 5.1
MiMo-V2.5
Provider
Z.ai (China)
Xiaomi (China)
Released
April 7, 2026
April 22, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
A core design strength of GLM 5.1.
Sustained tool use across thousands of calls
GLM 5.1
A core design strength of GLM 5.1.
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 5.1, 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 long-horizon autonomous agentic engineering (up to 8-hour runs)
→ GLM 5.1
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 5.1: 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 are real: 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.
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 5.1 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 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs), 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 5.1 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 either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) 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 5.1 or MiMo-V2.5?
MiMo-V2.5 is cheaper — $1.4/$4.4 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 10× 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 5.1 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.1, 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 5.1 or MiMo-V2.5?
MiMo-V2.5 — released April 22, 2026, about 15 days after GLM 5.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.