Ling 3.1 Flash vs MiMo-V2.5

InclusionAI (Ant Group) · China  |  Xiaomi · China · Updated June 2026

Quick verdict

Pick Ling 3.1 Flash for hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work or artificial analysis intelligence index score of 41 — above average for its price tier. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; Ling 3.1 Flash if you want a managed API.

Ling 3.1 Flash (InclusionAI (Ant Group)) and MiMo-V2.5 (Xiaomi) are two of the models people most often weigh against each other in 2026. Ling 3.1 Flash is inclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased. 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, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecLing 3.1 FlashMiMo-V2.5
ProviderInclusionAI (Ant Group) (China) Xiaomi (China)
ReleasedSeptember 30, 2026 April 22, 2026
Context window262K tokens (~393 pages) 1M (~1,500 pages)
Price (in/out)$0.3/$0.9 per 1M tokens $0.14/$0.28 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, code text, image, audio, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Hybrid-reasoning MoE — 560B total parameters, ~25B active per token, aimed at agents, tool use, and long-document work

Ling 3.1 Flash

MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)

Artificial Analysis Intelligence Index score of 41 — above average for its price tier

Ling 3.1 Flash

InclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased — and it is the newer of the two.

First-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok)

Ling 3.1 Flash

Ling 3.1 Flash lists first-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok) among its strengths; MiMo-V2.5 does not.

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 Ling 3.1 Flash ($0.3/$0.9 per 1M tokens), and that gap compounds at volume.

Agent-framework integration

MiMo-V2.5

Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it carries the larger 1M context.

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 3.8× larger than Ling 3.1 Flash's 262K tokens, 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 Ling 3.1 Flash, 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.

A team with data-privacy or self-hosting needs

→ MiMo-V2.5

Open weights let you run it on your own hardware; Ling 3.1 Flash is API-only.

Anyone whose priority is hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work

→ Ling 3.1 Flash

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.

Ling 3.1 Flash: where it fits

InclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased. Released September 30, 2026 by InclusionAI (Ant Group), it is built for hybrid-reasoning MoE — 560B total parameters, ~25B active per token, aimed at agents, tool use, and long-document work, artificial Analysis Intelligence Index score of 41 — above average for its price tier, first-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok), and predecessor Ling 3.0 Flash shipped MIT-licensed open weights, suggesting a similar path once 3.1 clears review.

Its trade-offs are real: shipped as an announcement plus a two-week free trial rather than a full release — no weights, no model card, and limited independent verification at launch, context window currently served at 262K tokens even though InclusionAI's stated target is 1M — the larger window isn't live yet, not yet open-weight despite InclusionAI saying it plans to open-source the model 'soon', and announced via WeChat rather than a formal English-language technical report, so some specs are vendor-reported only. At $0.3 in / $0.9 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

The defining split here is open vs. closed. MiMo-V2.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Ling 3.1 Flash 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 Ling 3.1 Flash 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.

See pricing

Frequently asked questions

Is Ling 3.1 Flash 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, Ling 3.1 Flash leans toward hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work 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, Ling 3.1 Flash or MiMo-V2.5?

MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Ling 3.1 Flash is API-metered at $0.3/$0.9 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?

MiMo-V2.5 — 1M vs 262K tokens, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Ling 3.1 Flash and MiMo-V2.5 together?

Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, 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, Ling 3.1 Flash or MiMo-V2.5?

Ling 3.1 Flash — released September 30, 2026, about 5 months after MiMo-V2.5.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.