Both are Xiaomi models. MiMo-V2.5-Pro is the newer, generally stronger default; reach for MiMo-V2.5 when its lower price or specific profile matters more than the latest capabilities.
MiMo-V2.5 and MiMo-V2.5-Pro are both Xiaomi models, so the real question is not which lab to trust but which tier fits your workload and budget. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: MiMo-V2.5 is about 3.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.435/$0.87 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Specifications
Spec
MiMo-V2.5
MiMo-V2.5-Pro
Provider
Xiaomi (China)
Xiaomi (China)
Released
April 22, 2026
April 22, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, audio, video, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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.
Complex software engineering (top-ranked on SWE-bench Pro): MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
Long-horizon autonomous tasks (1,000+ tool calls): MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
Strong on GDPVal and ClawEval: MiMo-V2.5-Pro — A core design strength of MiMo-V2.5-Pro.
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.
Which should you pick?
A cost-sensitive startup shipping high volume: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts MiMo-V2.5-Pro, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is native omnimodal — strong image and video understanding: MiMo-V2.5 — It is specifically built for that.
Anyone whose priority is complex software engineering (top-ranked on swe-bench pro): MiMo-V2.5-Pro — That is its strongest area.
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 are real: 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.
MiMo-V2.5-Pro: where it fits
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Released April 22, 2026 by Xiaomi, it is built for complex software engineering (top-ranked on SWE-bench Pro), long-horizon autonomous tasks (1,000+ tool calls), strong on GDPVal and ClawEval, and agent-framework integration.
Its trade-offs: benchmark rankings are largely vendor-stated, and limited Western adoption and tooling. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because MiMo-V2.5 and MiMo-V2.5-Pro come from the same lab (Xiaomi), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. MiMo-V2.5-Pro is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to MiMo-V2.5-Pro and drop down only with a concrete reason.
Frequently asked questions
Is MiMo-V2.5 or MiMo-V2.5-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, MiMo-V2.5 leans toward native omnimodal — strong image and video understanding while MiMo-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or MiMo-V2.5-Pro?
MiMo-V2.5 is cheaper — $0.14/$0.28 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from MiMo-V2.5-Pro to MiMo-V2.5?
Since both are Xiaomi models, the newer one (MiMo-V2.5-Pro) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, MiMo-V2.5 or MiMo-V2.5-Pro?
They were released around the same time (April 22, 2026 and April 22, 2026).
MiMo-V2.5 vs MiMo-V2.5-Pro
Xiaomi · China | Xiaomi · China · Updated June 2026
Quick verdict
Both are Xiaomi models. MiMo-V2.5-Pro is the newer, generally stronger default; reach for MiMo-V2.5 when its lower price or specific profile matters more than the latest capabilities.
MiMo-V2.5 and MiMo-V2.5-Pro are both Xiaomi models, so the real question is not which lab to trust but which tier fits your workload and budget. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Price: MiMo-V2.5 is about 3.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.435/$0.87 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Side-by-side specs
Spec
MiMo-V2.5
MiMo-V2.5-Pro
Provider
Xiaomi (China)
Xiaomi (China)
Released
April 22, 2026
April 22, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, audio, video, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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.
Complex software engineering (top-ranked on SWE-bench Pro)
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
Long-horizon autonomous tasks (1,000+ tool calls)
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
Strong on GDPVal and ClawEval
MiMo-V2.5-Pro
A core design strength of MiMo-V2.5-Pro.
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts MiMo-V2.5-Pro, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
It is specifically built for that.
Anyone whose priority is complex software engineering (top-ranked on swe-bench pro)
→ MiMo-V2.5-Pro
That is its strongest area.
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 are real: 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.
MiMo-V2.5-Pro: where it fits
Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost. Released April 22, 2026 by Xiaomi, it is built for complex software engineering (top-ranked on SWE-bench Pro), long-horizon autonomous tasks (1,000+ tool calls), strong on GDPVal and ClawEval, and agent-framework integration.
Its trade-offs: benchmark rankings are largely vendor-stated, and limited Western adoption and tooling. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because MiMo-V2.5 and MiMo-V2.5-Pro come from the same lab (Xiaomi), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. MiMo-V2.5-Pro is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to MiMo-V2.5-Pro and drop down only with a concrete reason.
Want both MiMo-V2.5 and MiMo-V2.5-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, MiMo-V2.5 leans toward native omnimodal — strong image and video understanding while MiMo-V2.5-Pro leans toward complex software engineering (top-ranked on swe-bench pro), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or MiMo-V2.5-Pro?
MiMo-V2.5 is cheaper — $0.14/$0.28 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from MiMo-V2.5-Pro to MiMo-V2.5?
Since both are Xiaomi models, the newer one (MiMo-V2.5-Pro) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, MiMo-V2.5 or MiMo-V2.5-Pro?
They were released around the same time (April 22, 2026 and April 22, 2026).
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.