Kimi K2.6 vs Kimi K3.1 Pro
Moonshot AI · China | Moonshot AI · China · Updated June 2026
Quick verdict
Both are Moonshot AI models. Kimi K3.1 Pro is the newer, generally stronger default; reach for Kimi K2.6 when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Kimi K2.6 and Kimi K3.1 Pro 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 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. 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
- ▸Price: Kimi K2.6 is about 2.1× cheaper on input ($0.95/$4 per 1M tokens vs $2/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: Kimi K3.1 Pro holds 4× more — 1M tokens (~1,573 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 K3.1 Pro is the newer model by about 6 months (released October 23, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Kimi K2.6 | Kimi K3.1 Pro |
|---|---|---|
| Provider | Moonshot AI (China) | Moonshot AI (China) |
| Released | April 20, 2026 | October 23, 2026 |
| Context window | 256K (~393 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $0.95/$4 per 1M tokens | $2/$10 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, image, video, code | text, image, 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
Open weights make this possible at all — Kimi K3.1 Pro is API-only, so it cannot leave the vendor's servers.
Multi-agent swarms (scales to ~300 sub-agents)
Kimi K2.6
At $0.95/$4 per 1M tokens it undercuts Kimi K3.1 Pro ($2/$10 per 1M tokens), and that gap compounds at volume.
Self-hosting and data-residency control
Kimi K2.6
Kimi K3.1 Pro is comparatively weak here — self-hosting is impractical - about 1.4 TB of raw weights even at 4-bit
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 carries the larger 1M tokens context.
Terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis
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.
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 K2.6 is comparatively weak here — 256K context trails the 1M Claude and Gemini flagships
Lowest cost at scale
Kimi K2.6
At $0.95/$4 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Kimi K3.1 Pro
Its 1M tokens window is about 4× larger than Kimi K2.6's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Kimi K2.6
At $0.95/$4 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
→ Kimi K2.6
Open weights let you run it on your own hardware; Kimi K3.1 Pro is API-only.
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 sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base
→ Kimi K3.1 Pro
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 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: 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.
The bottom line for this matchup
Because Kimi K2.6 and Kimi K3.1 Pro come from the same lab (Moonshot AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Kimi K3.1 Pro 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 K3.1 Pro and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Kimi K2.6 or Kimi K3.1 Pro better for coding?
Public SWE-Bench figures are not available for Kimi K3.1 Pro, 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 K3.1 Pro leans toward sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K2.6 or Kimi K3.1 Pro?
Kimi K2.6 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?
Kimi K3.1 Pro — 1M tokens vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Kimi K2.6 to Kimi K3.1 Pro?
Since both are Moonshot AI models, the newer one (Kimi K3.1 Pro) 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 K3.1 Pro?
Kimi K3.1 Pro — released October 23, 2026, about 6 months 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.