Kimi K2.6 vs Kimi K2.7 Code
Moonshot AI · China | Moonshot AI · China · Updated June 2026
Quick verdict
Both are Moonshot AI models. Kimi K2.7 Code is the newer, generally stronger default; reach for Kimi K2.6 when a specific cost or latency profile matters more than the latest capabilities.
Kimi K2.6 and Kimi K2.7 Code are both Moonshot AI models, so the real question is not which lab to trust but which tier fits your workload and budget. Kimi K2.6 is moonshot's open-weight 1T-parameter (32B active) MoE model — frontier-class agentic coding you can download and self-host. 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. 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 K2.7 Code is the newer model by about 53 days (released June 12, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Kimi K2.6 | Kimi K2.7 Code |
|---|---|---|
| Provider | Moonshot AI (China) | Moonshot AI (China) |
| Released | April 20, 2026 | June 12, 2026 |
| Context window | 256K (~393 pages) | 256K (~393 pages) |
| Price (in/out) | $0.95/$4 per 1M tokens | $0.95/$4 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, video, code | text, image, video, code |
| SWE-Bench Verified | 80.2% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Open-weight agentic coding and long-horizon tasks
Kimi K2.6
Kimi K2.6 lists open-weight agentic coding and long-horizon tasks among its strengths; Kimi K2.7 Code does not.
Multi-agent swarms (scales to ~300 sub-agents)
Kimi K2.6
Kimi K2.6 lists multi-agent swarms (scales to ~300 sub-agents) among its strengths; Kimi K2.7 Code does not.
Self-hosting and data-residency control
Kimi K2.6
Kimi K2.6 lists self-hosting and data-residency control among its strengths; Kimi K2.7 Code does not.
Long-horizon agentic software engineering
Kimi K2.7 Code
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 — and it is the newer of the two.
Token-efficient reasoning (~30% fewer than K2.6)
Kimi K2.7 Code
Kimi K2.7 Code lists token-efficient reasoning (~30% fewer than K2.6) among its strengths; Kimi K2.6 does not.
Open-weight 1T MoE, self-hostable
Kimi K2.7 Code
Kimi K2.7 Code lists open-weight 1T MoE, self-hostable among its strengths; Kimi K2.6 does not.
Which should you pick?
Anyone whose priority is open-weight agentic coding and long-horizon tasks
→ Kimi K2.6
It is specifically built for that.
Anyone whose priority is long-horizon agentic software engineering
→ Kimi K2.7 Code
That is its strongest area.
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 are real: 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 $0.95 in / $4 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
Because Kimi K2.6 and Kimi K2.7 Code come from the same lab (Moonshot AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Kimi K2.7 Code 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 K2.7 Code and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Kimi K2.6 or Kimi K2.7 Code better for coding?
Public SWE-Bench figures are not available for Kimi K2.7 Code, so the honest test is your own repository — run an identical real bug through both. By design, Kimi K2.6 leans toward open-weight agentic coding and long-horizon tasks while Kimi K2.7 Code leans toward long-horizon agentic software engineering, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.6 or Kimi K2.7 Code?
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 K2.6 to Kimi K2.7 Code?
Since both are Moonshot AI models, the newer one (Kimi K2.7 Code) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Kimi K2.6 or Kimi K2.7 Code?
Kimi K2.7 Code — released June 12, 2026, about 53 days after Kimi K2.6.
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.