Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. On a tight budget at scale, MiMo-V2.5 is the value pick.
MiMo-V2.5 (Xiaomi) and MiniMax M3 (MiniMax) are two of the models people most often weigh against each other in 2026. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 2.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.3/$1.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: MiniMax M3 is the newer model by about 40 days (released June 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
MiMo-V2.5
MiniMax M3
Provider
Xiaomi (China)
MiniMax (China)
Released
April 22, 2026
June 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.3/$1.2 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 — Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts MiniMax M3 ($0.3/$1.2 per 1M tokens), and that gap compounds at volume.
Agent-framework integration: MiMo-V2.5 — MiMo-V2.5 lists agent-framework integration among its strengths; MiniMax M3 does not.
Open-weight 428B MoE (~23B active per token) with a 1M-token context: MiniMax M3 — MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it is the newer of the two.
Native multimodal input — text, image and video: MiniMax M3 — MiniMax M3 lists native multimodal input — text, image and video among its strengths; MiMo-V2.5 does not.
Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5: MiniMax M3 — MiniMax M3 lists reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5 among its strengths; MiMo-V2.5 does not.
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 MiniMax M3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiniMax M3 — Larger 1M window fits more in one prompt.
Anyone whose priority is native omnimodal — strong image and video understanding: MiMo-V2.5 — It is specifically built for that.
Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context: MiniMax M3 — 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.
MiniMax M3: where it fits
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released June 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.
Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
MiMo-V2.5 and MiniMax M3 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiniMax M3 holds the larger context; and each leads in its own area — MiMo-V2.5 for native omnimodal — strong image and video understanding, MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is MiMo-V2.5 or MiniMax M3 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 MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or MiniMax M3?
MiMo-V2.5 is cheaper — $0.14/$0.28 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 2.1× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both MiMo-V2.5 and MiniMax M3 together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5, MiniMax M3 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, MiMo-V2.5 or MiniMax M3?
MiniMax M3 — released June 2026, about 40 days after MiMo-V2.5.
MiMo-V2.5 vs MiniMax M3
Xiaomi · China | MiniMax · China · Updated June 2026
Quick verdict
Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. On a tight budget at scale, MiMo-V2.5 is the value pick.
MiMo-V2.5 (Xiaomi) and MiniMax M3 (MiniMax) are two of the models people most often weigh against each other in 2026. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. 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 2.1× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.3/$1.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: MiniMax M3 is the newer model by about 40 days (released June 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
MiMo-V2.5
MiniMax M3
Provider
Xiaomi (China)
MiniMax (China)
Released
April 22, 2026
June 2026
Context window
1M (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$0.14/$0.28 per 1M tokens
$0.3/$1.2 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
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts MiniMax M3 ($0.3/$1.2 per 1M tokens), and that gap compounds at volume.
Agent-framework integration
MiMo-V2.5
MiMo-V2.5 lists agent-framework integration among its strengths; MiniMax M3 does not.
Open-weight 428B MoE (~23B active per token) with a 1M-token context
MiniMax M3
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it is the newer of the two.
Native multimodal input — text, image and video
MiniMax M3
MiniMax M3 lists native multimodal input — text, image and video among its strengths; MiMo-V2.5 does not.
Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5
MiniMax M3
MiniMax M3 lists reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5 among its strengths; MiMo-V2.5 does not.
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 MiniMax M3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiniMax M3
Larger 1M window fits more in one prompt.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
It is specifically built for that.
Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context
→ MiniMax M3
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.
MiniMax M3: where it fits
MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released June 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.
Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
MiMo-V2.5 and MiniMax M3 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiniMax M3 holds the larger context; and each leads in its own area — MiMo-V2.5 for native omnimodal — strong image and video understanding, MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both MiMo-V2.5 and MiniMax M3 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 MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MiMo-V2.5 or MiniMax M3?
MiMo-V2.5 is cheaper — $0.14/$0.28 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 2.1× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both MiMo-V2.5 and MiniMax M3 together?
Yes — a multi-model platform like LumiChats gives you MiMo-V2.5, MiniMax M3 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, MiMo-V2.5 or MiniMax M3?
MiniMax M3 — released June 2026, about 40 days after MiMo-V2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.