Pick Kimi K2.7 Code for long-horizon agentic software engineering or token-efficient reasoning (~30% fewer than k2.6). Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, MiMo-V2.5 is the value pick.
Kimi K2.7 Code (Moonshot AI) and MiMo-V2.5 (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 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 and context window — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 6.8× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.95/$4 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: MiMo-V2.5 holds 3.8× more — 1M (~1,500 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Kimi K2.7 Code is the newer model by about 51 days (released June 12, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Kimi K2.7 Code
MiMo-V2.5
Provider
Moonshot AI (China)
Xiaomi (China)
Released
June 12, 2026
April 22, 2026
Context window
256K (~393 pages)
1M (~1,500 pages)
Price (in/out)
$0.95/$4 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, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not 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.
Native omnimodal — strong image and video understanding: MiMo-V2.5 — A core design strength of MiMo-V2.5.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — A core design strength of MiMo-V2.5.
Agent-framework integration: MiMo-V2.5 — A core design strength of MiMo-V2.5.
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, 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 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 — 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 native omnimodal — strong image and video understanding: MiMo-V2.5 — 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: 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
Kimi K2.7 Code and MiMo-V2.5 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiMo-V2.5 holds the larger context; and each leads in its own area — Kimi K2.7 Code for long-horizon agentic software engineering, MiMo-V2.5 for native omnimodal — strong image and video understanding. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Kimi K2.7 Code 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, Kimi K2.7 Code leans toward long-horizon agentic software engineering 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, Kimi K2.7 Code or MiMo-V2.5?
MiMo-V2.5 is cheaper — $0.95/$4 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 6.8× apart on input.
Which has the bigger context window?
MiMo-V2.5 — 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 together?
Yes — a multi-model platform like LumiChats gives you Kimi K2.7 Code, 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, Kimi K2.7 Code or MiMo-V2.5?
Kimi K2.7 Code — released June 12, 2026, about 51 days after MiMo-V2.5.
Kimi K2.7 Code vs MiMo-V2.5
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 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). On a tight budget at scale, MiMo-V2.5 is the value pick.
Kimi K2.7 Code (Moonshot AI) and MiMo-V2.5 (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 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 and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiMo-V2.5 is about 6.8× cheaper on input ($0.14/$0.28 per 1M tokens vs $0.95/$4 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: MiMo-V2.5 holds 3.8× more — 1M (~1,500 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Kimi K2.7 Code is the newer model by about 51 days (released June 12, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Kimi K2.7 Code
MiMo-V2.5
Provider
Moonshot AI (China)
Xiaomi (China)
Released
June 12, 2026
April 22, 2026
Context window
256K (~393 pages)
1M (~1,500 pages)
Price (in/out)
$0.95/$4 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, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not 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.
Native omnimodal — strong image and video understanding
MiMo-V2.5
A core design strength of MiMo-V2.5.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
A core design strength of MiMo-V2.5.
Agent-framework integration
MiMo-V2.5
A core design strength of MiMo-V2.5.
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, 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 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
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 native omnimodal — strong image and video understanding
→ MiMo-V2.5
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: 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
Kimi K2.7 Code and MiMo-V2.5 overlap enough that the right pick depends on your specific job. MiMo-V2.5 costs less per token; MiMo-V2.5 holds the larger context; and each leads in its own area — Kimi K2.7 Code for long-horizon agentic software engineering, MiMo-V2.5 for native omnimodal — strong image and video understanding. 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 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, Kimi K2.7 Code leans toward long-horizon agentic software engineering 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, Kimi K2.7 Code or MiMo-V2.5?
MiMo-V2.5 is cheaper — $0.95/$4 per 1M tokens vs $0.14/$0.28 per 1M tokens, roughly 6.8× apart on input.
Which has the bigger context window?
MiMo-V2.5 — 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 together?
Yes — a multi-model platform like LumiChats gives you Kimi K2.7 Code, 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, Kimi K2.7 Code or MiMo-V2.5?
Kimi K2.7 Code — released June 12, 2026, about 51 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.