Both are Moonshot AI models. Kimi K2.6 is the newer, generally stronger default; reach for Kimi K2.5 when a specific cost or latency profile matters more than the latest capabilities.
Kimi K2.5 and Kimi K2.6 are both Moonshot AI models, so the real question is not which lab to trust but which tier fits your workload and budget. Kimi K2.5 is moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Kimi K2.6 is moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Context window: both advertise 256K (~393 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Kimi K2.6 is the newer model by about 3 months (released April 20, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Kimi K2.5
Kimi K2.6
Provider
Moonshot AI (China)
Moonshot AI (China)
Released
January 27, 2026
April 20, 2026
Context window
256K (~393 pages)
256K (~393 pages)
Price (in/out)
$0.6/$2.5 per 1M tokens
$0.6/$2.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
80.2%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Native multimodal reasoning and visual coding: Kimi K2.5 — Kimi K2.6 is comparatively weak here — weaker on single-turn vision and grounded multimodal tasks
Agentic tool-calling and self-directed multi-step work: Kimi K2.5 — Kimi K2.5 lists agentic tool-calling and self-directed multi-step work among its strengths; Kimi K2.6 does not.
Open-weight (Modified-MIT) — self-hostable at 256K context: Kimi K2.5 — Kimi K2.6 is comparatively weak here — 256K context trails the 1M Claude and Gemini flagships
Open-weight agentic coding and long-horizon tasks: Kimi K2.6 — Kimi K2.5 is comparatively weak here — its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol
Multi-agent swarms (scales to ~300 sub-agents): Kimi K2.6 — Moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host — and it is the newer of the two.
Self-hosting and data-residency control: Kimi K2.6 — Kimi K2.6 lists self-hosting and data-residency control among its strengths; Kimi K2.5 does not.
Which should you pick?
Anyone whose priority is native multimodal reasoning and visual coding: Kimi K2.5 — It is specifically built for that.
Anyone whose priority is open-weight agentic coding and long-horizon tasks: Kimi K2.6 — That is its strongest area.
Kimi K2.5: where it fits
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Released January 27, 2026 by Moonshot AI, it is built for native multimodal reasoning and visual coding, agentic tool-calling and self-directed multi-step work, open-weight (Modified-MIT) — self-hostable at 256K context, and vendor reports around 76.8% on its own SWE-agent coding harness.
Its trade-offs are real: its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol, superseded within Moonshot's line by Kimi K2.6 and K2.7, openRouter shows a promo price below Moonshot's $0.60/$2.50 list, and image input but no audio or video. At $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
Kimi K2.6: where it fits
Moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host. Released April 20, 2026 by Moonshot AI, it is built for open-weight agentic coding and long-horizon tasks, multi-agent swarms (scales to ~300 sub-agents), self-hosting and data-residency control, and strong price-to-performance across many API providers.
Its trade-offs: 256K context trails the 1M Claude and Gemini flagships, weaker on single-turn vision and grounded multimodal tasks, and chinese-jurisdiction data and newer vendor track record. At $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Kimi K2.5 and Kimi K2.6 come from the same lab (Moonshot AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Kimi K2.6 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Kimi K2.6 and drop down only with a concrete reason.
Frequently asked questions
Is Kimi K2.5 or Kimi K2.6 better for coding?
Public SWE-Bench figures are not available for Kimi K2.5, so the honest test is your own repository — run an identical real bug through both. By design, Kimi K2.5 leans toward native multimodal reasoning and visual coding while Kimi K2.6 leans toward open-weight agentic coding and long-horizon tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.5 or Kimi K2.6?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Both advertise 256K (~393 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Kimi K2.5 to Kimi K2.6?
Since both are Moonshot AI models, the newer one (Kimi K2.6) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Kimi K2.5 or Kimi K2.6?
Kimi K2.6 — released April 20, 2026, about 3 months after Kimi K2.5.
Kimi K2.5 vs Kimi K2.6
Moonshot AI · China | Moonshot AI · China · Updated June 2026
Quick verdict
Both are Moonshot AI models. Kimi K2.6 is the newer, generally stronger default; reach for Kimi K2.5 when a specific cost or latency profile matters more than the latest capabilities.
Kimi K2.5 and Kimi K2.6 are both Moonshot AI models, so the real question is not which lab to trust but which tier fits your workload and budget. Kimi K2.5 is moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Kimi K2.6 is moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Context window: both advertise 256K (~393 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Kimi K2.6 is the newer model by about 3 months (released April 20, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Kimi K2.5
Kimi K2.6
Provider
Moonshot AI (China)
Moonshot AI (China)
Released
January 27, 2026
April 20, 2026
Context window
256K (~393 pages)
256K (~393 pages)
Price (in/out)
$0.6/$2.5 per 1M tokens
$0.6/$2.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
80.2%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Native multimodal reasoning and visual coding
Kimi K2.5
Kimi K2.6 is comparatively weak here — weaker on single-turn vision and grounded multimodal tasks
Agentic tool-calling and self-directed multi-step work
Kimi K2.5
Kimi K2.5 lists agentic tool-calling and self-directed multi-step work among its strengths; Kimi K2.6 does not.
Open-weight (Modified-MIT) — self-hostable at 256K context
Kimi K2.5
Kimi K2.6 is comparatively weak here — 256K context trails the 1M Claude and Gemini flagships
Open-weight agentic coding and long-horizon tasks
Kimi K2.6
Kimi K2.5 is comparatively weak here — its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol
Multi-agent swarms (scales to ~300 sub-agents)
Kimi K2.6
Moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host — and it is the newer of the two.
Self-hosting and data-residency control
Kimi K2.6
Kimi K2.6 lists self-hosting and data-residency control among its strengths; Kimi K2.5 does not.
Which should you pick?
Anyone whose priority is native multimodal reasoning and visual coding
→ Kimi K2.5
It is specifically built for that.
Anyone whose priority is open-weight agentic coding and long-horizon tasks
→ Kimi K2.6
That is its strongest area.
Kimi K2.5: where it fits
Moonshot's open-weight multimodal model at $0.60/$2.50 with a 256K window — strong visual coding and agentic work, since superseded by K2.6/K2.7. Released January 27, 2026 by Moonshot AI, it is built for native multimodal reasoning and visual coding, agentic tool-calling and self-directed multi-step work, open-weight (Modified-MIT) — self-hostable at 256K context, and vendor reports around 76.8% on its own SWE-agent coding harness.
Its trade-offs are real: its coding score uses Moonshot's own harness, not the standard SWE-Bench Verified protocol, superseded within Moonshot's line by Kimi K2.6 and K2.7, openRouter shows a promo price below Moonshot's $0.60/$2.50 list, and image input but no audio or video. At $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
Kimi K2.6: where it fits
Moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host. Released April 20, 2026 by Moonshot AI, it is built for open-weight agentic coding and long-horizon tasks, multi-agent swarms (scales to ~300 sub-agents), self-hosting and data-residency control, and strong price-to-performance across many API providers.
Its trade-offs: 256K context trails the 1M Claude and Gemini flagships, weaker on single-turn vision and grounded multimodal tasks, and chinese-jurisdiction data and newer vendor track record. At $0.6 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Kimi K2.5 and Kimi K2.6 come from the same lab (Moonshot AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Kimi K2.6 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Kimi K2.6 and drop down only with a concrete reason.
Want both Kimi K2.5 and Kimi K2.6 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 Kimi K2.5, so the honest test is your own repository — run an identical real bug through both. By design, Kimi K2.5 leans toward native multimodal reasoning and visual coding while Kimi K2.6 leans toward open-weight agentic coding and long-horizon tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.5 or Kimi K2.6?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Both advertise 256K (~393 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Kimi K2.5 to Kimi K2.6?
Since both are Moonshot AI models, the newer one (Kimi K2.6) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Kimi K2.5 or Kimi K2.6?
Kimi K2.6 — released April 20, 2026, about 3 months after Kimi K2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.