Kimi K3.1 Pro vs MiMo-V2.5-Pro

Moonshot AI · China  |  Xiaomi · China · Updated June 2026

Quick verdict

Pick Kimi K3.1 Pro for sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base or terminal-bench 4.0 of 65.7% (moonshot) and 67% as measured by artificial analysis. Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). Choose MiMo-V2.5-Pro if you need self-hosting or data privacy; Kimi K3.1 Pro if you want a managed API.

Kimi K3.1 Pro (Moonshot AI) and MiMo-V2.5-Pro (Xiaomi) are two of the models people most often weigh against each other in 2026. Kimi K3.1 Pro is moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4. MiMo-V2.5-Pro is xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier 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

SpecKimi K3.1 ProMiMo-V2.5-Pro
ProviderMoonshot AI (China) Xiaomi (China)
ReleasedOctober 23, 2026 April 22, 2026
Context window1M tokens (~1,573 pages) 1M (~1,500 pages)
Price (in/out)$2/$10 per 1M tokens $0.435/$0.87 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Sparse MoE with 2.8T total and about 104B active parameters, post-trained from the Kimi K3 base

Kimi K3.1 Pro

Moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4 — and it is the newer of the two.

Terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis

Kimi K3.1 Pro

MiMo-V2.5-Pro is comparatively weak here — benchmark rankings are largely vendor-stated

Artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists

Kimi K3.1 Pro

Kimi K3.1 Pro lists artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists among its strengths; MiMo-V2.5-Pro does not.

Complex software engineering (top-ranked on SWE-bench Pro)

MiMo-V2.5-Pro

Kimi K3.1 Pro is comparatively weak here — most benchmarks are internal or use differing harnesses; no SWE-bench Verified figure published

Long-horizon autonomous tasks (1,000+ tool calls)

MiMo-V2.5-Pro

Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and it runs cheaper at $0.435/$0.87 per 1M tokens.

Strong on GDPVal and ClawEval

MiMo-V2.5-Pro

Xiaomi's flagship agentic model — autonomous, long-horizon software engineering at a fraction of frontier cost — and its weights are open while Kimi K3.1 Pro is API-only.

Lowest cost at scale

MiMo-V2.5-Pro

At $0.435/$0.87 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-Pro

At $0.435/$0.87 per 1M tokens it undercuts Kimi K3.1 Pro, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Kimi K3.1 Pro

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ MiMo-V2.5-Pro

Open weights let you run it on your own hardware; Kimi K3.1 Pro is API-only.

Anyone whose priority is sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base

→ Kimi K3.1 Pro

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.

Kimi K3.1 Pro: where it fits

Moonshot's October 23, 2026 post-training upgrade to Kimi K3 - a 2.8T-parameter MoE at $2/$10 with open weights promised by November 4. Released October 23, 2026 by Moonshot AI, it is built for sparse MoE with 2.8T total and about 104B active parameters, post-trained from the Kimi K3 base, terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis, artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists, and standard API price cut by a third versus K3 to $2/$10 per million tokens (Highspeed tier $4/$20).

Its trade-offs are real: weights promised by November 4, 2026 and not confirmed public as of November 3; license terms not yet disclosed, very high output-token use: roughly 150M output tokens across the Artificial Analysis index, self-hosting is impractical - about 1.4 TB of raw weights even at 4-bit, and most benchmarks are internal or use differing harnesses; no SWE-bench Verified figure published. At $2 in / $10 out per million tokens, it sits in the mid 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

The defining split here is open vs. closed. MiMo-V2.5-Pro gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Kimi K3.1 Pro 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 Kimi K3.1 Pro 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.

See pricing

Frequently asked questions

Is Kimi K3.1 Pro 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, Kimi K3.1 Pro leans toward sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base 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, Kimi K3.1 Pro or MiMo-V2.5-Pro?

MiMo-V2.5-Pro is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Kimi K3.1 Pro is API-metered at $2/$10 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?

Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Kimi K3.1 Pro and MiMo-V2.5-Pro together?

Yes — a multi-model platform like LumiChats gives you Kimi K3.1 Pro, MiMo-V2.5-Pro 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 K3.1 Pro or MiMo-V2.5-Pro?

Kimi K3.1 Pro — released October 23, 2026, about 6 months after MiMo-V2.5-Pro.

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.