Kimi K2.7 Code vs MiMo-V2.5-Pro

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

Quick verdict

Pick Kimi K2.7 Code for long-horizon agentic software engineering or token-efficient reasoning (~30% fewer than k2.6). Pick MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro) or long-horizon autonomous tasks (1,000+ tool calls). On a tight budget at scale, MiMo-V2.5-Pro is the value pick.

Kimi K2.7 Code (Moonshot AI) and MiMo-V2.5-Pro (Xiaomi) are two of the models people most often weigh against each other in 2026. Kimi K2.7 Code is moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. 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 and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecKimi K2.7 CodeMiMo-V2.5-Pro
ProviderMoonshot AI (China) Xiaomi (China)
ReleasedJune 12, 2026 April 22, 2026
Context window256K (~393 pages) 1M (~1,500 pages)
Price (in/out)$0.95/$4 per 1M tokens $0.435/$0.87 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, video, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon agentic software engineering

Kimi K2.7 Code

A core design strength of Kimi K2.7 Code.

Token-efficient reasoning (~30% fewer than K2.6)

Kimi K2.7 Code

A core design strength of Kimi K2.7 Code.

Open-weight 1T MoE, self-hostable

Kimi K2.7 Code

A core design strength of Kimi K2.7 Code.

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-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.

Largest single-prompt input

MiMo-V2.5-Pro

Its 1M window is about 3.8× larger, fitting roughly 1,500 pages in one prompt.

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 K2.7 Code, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

MiMo-V2.5-Pro

Larger 1M window fits more in one prompt.

Anyone whose priority is long-horizon agentic software engineering

Kimi K2.7 Code

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 K2.7 Code: where it fits

Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. Released June 12, 2026 by Moonshot AI, it is built for long-horizon agentic software engineering, token-efficient reasoning (~30% fewer than K2.6), open-weight 1T MoE, self-hostable, and multi-turn tool use with preserved reasoning.

Its trade-offs are real: only self-reported benchmarks; no SWE-Bench Verified, and thinking mode and sampling params can't be disabled. At $0.95 in / $4 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

Kimi K2.7 Code and MiMo-V2.5-Pro overlap enough that the right pick depends on your specific job. MiMo-V2.5-Pro costs less per token; MiMo-V2.5-Pro holds the larger context; and each leads in its own area — Kimi K2.7 Code for long-horizon agentic software engineering, MiMo-V2.5-Pro for complex software engineering (top-ranked on swe-bench pro). Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Kimi K2.7 Code 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 K2.7 Code 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 K2.7 Code leans toward long-horizon agentic software engineering 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 K2.7 Code or MiMo-V2.5-Pro?

MiMo-V2.5-Pro is cheaper — $0.95/$4 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 2.2× apart on input.

Which has the bigger context window?

MiMo-V2.5-Pro — 1M vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Kimi K2.7 Code and MiMo-V2.5-Pro together?

Yes — a multi-model platform like LumiChats gives you Kimi K2.7 Code, 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 K2.7 Code or MiMo-V2.5-Pro?

Kimi K2.7 Code — released June 12, 2026, about 51 days 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.