Kimi K3 vs MiMo-V2.6-Flash
Moonshot AI · China | Xiaomi · China · Updated June 2026
Quick verdict
Pick Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). Pick MiMo-V2.6-Flash for same natively omnimodal design as pro (text, image, video, audio) at a fraction of the size and price or 309b total parameters, 15b active per token (sparse moe) — a hybrid attention mechanism for efficiency. On a tight budget at scale, MiMo-V2.6-Flash is the value pick.
Kimi K3 (Moonshot AI) and MiMo-V2.6-Flash (Xiaomi) are two of the models people most often weigh against each other in 2026. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. MiMo-V2.6-Flash is xiaomi's efficient omnimodal MoE model — 309B parameters, 15B active, MIT-licensed, priced at $0.14/$0.28 per million tokens. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: MiMo-V2.6-Flash is about 21× cheaper on input ($0.14/$0.28 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: both advertise 1M (~1,573 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: MiMo-V2.6-Flash is the newer model by about 56 days (released September 21, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Kimi K3 | MiMo-V2.6-Flash |
|---|---|---|
| Provider | Moonshot AI (China) | Xiaomi (China) |
| Released | July 27, 2026 | September 21, 2026 |
| Context window | 1M (~1,573 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $3/$15 per 1M tokens | $0.14/$0.28 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, video, code | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Largest open-weight model at release — 2.8T sparse MoE, self-hostable
Kimi K3
Kimi K3 lists largest open-weight model at release — 2.8T sparse MoE, self-hostable among its strengths; MiMo-V2.6-Flash does not.
1M-token context with native vision (text, image and video)
Kimi K3
Kimi K3 lists 1M-token context with native vision (text, image and video) among its strengths; MiMo-V2.6-Flash does not.
Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness
Kimi K3
MiMo-V2.6-Flash is comparatively weak here — same caveat as Pro: benchmark claims are largely self-reported by Xiaomi at launch, not yet independently verified at scale
Same natively omnimodal design as Pro (text, image, video, audio) at a fraction of the size and price
MiMo-V2.6-Flash
At $0.14/$0.28 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.
309B total parameters, 15B active per token (sparse MoE) — a hybrid attention mechanism for efficiency
MiMo-V2.6-Flash
Xiaomi's efficient omnimodal MoE model — 309B parameters, 15B active, MIT-licensed, priced at $0.14/$0.28 per million tokens — and it runs cheaper at $0.14/$0.28 per 1M tokens.
MIT-licensed, self-hostable, and among the cheapest omnimodal options at $0.14/$0.28 per million tokens
MiMo-V2.6-Flash
Xiaomi's efficient omnimodal MoE model — 309B parameters, 15B active, MIT-licensed, priced at $0.14/$0.28 per million tokens — and it is the newer of the two.
Lowest cost at scale
MiMo-V2.6-Flash
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-V2.6-Flash
At $0.14/$0.28 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is largest open-weight model at release — 2.8t sparse moe, self-hostable
→ Kimi K3
It is specifically built for that.
Anyone whose priority is same natively omnimodal design as pro (text, image, video, audio) at a fraction of the size and price
→ MiMo-V2.6-Flash
That is its strongest area.
Kimi K3: where it fits
Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.
Its trade-offs are real: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.
MiMo-V2.6-Flash: where it fits
Xiaomi's efficient omnimodal MoE model — 309B parameters, 15B active, MIT-licensed, priced at $0.14/$0.28 per million tokens. Released September 21, 2026 by Xiaomi, it is built for same natively omnimodal design as Pro (text, image, video, audio) at a fraction of the size and price, 309B total parameters, 15B active per token (sparse MoE) — a hybrid attention mechanism for efficiency, and mIT-licensed, self-hostable, and among the cheapest omnimodal options at $0.14/$0.28 per million tokens.
Its trade-offs: lower capacity than Pro — expect a real quality gap on the hardest reasoning and generation tasks, and same caveat as Pro: benchmark claims are largely self-reported by Xiaomi at launch, not yet independently verified at scale. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Kimi K3 and MiMo-V2.6-Flash overlap enough that the right pick depends on your specific job. MiMo-V2.6-Flash costs less per token; and each leads in its own area — Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable, MiMo-V2.6-Flash for same natively omnimodal design as pro (text, image, video, audio) at a fraction of the size and price. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Kimi K3 and MiMo-V2.6-Flash 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 pricingFrequently asked questions
Is Kimi K3 or MiMo-V2.6-Flash 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, Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable while MiMo-V2.6-Flash leans toward same natively omnimodal design as pro (text, image, video, audio) at a fraction of the size and price, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K3 or MiMo-V2.6-Flash?
MiMo-V2.6-Flash is cheaper — $3/$15 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 21× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,573 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Kimi K3 and MiMo-V2.6-Flash together?
Yes — a multi-model platform like LumiChats gives you Kimi K3, MiMo-V2.6-Flash 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, Kimi K3 or MiMo-V2.6-Flash?
MiMo-V2.6-Flash — released September 21, 2026, about 56 days after Kimi K3.
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.