Kimi K3.1 Pro vs LongCat-2.0

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

Quick verdict

Pick Kimi K3.1 Pro for sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base or terminal-bench 4.0 of 65.7% (moonshot) and 67% as measured by artificial analysis. Pick LongCat-2.0 for near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months or massive native 1m context at near-linear cost via sparse attention. Choose LongCat-2.0 if you need self-hosting or data privacy; Kimi K3.1 Pro if you want a managed API.

Kimi K3.1 Pro (Moonshot AI) and LongCat-2.0 (Meituan) are two of the models people most often weigh against each other in 2026. 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. LongCat-2.0 is a trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecKimi K3.1 ProLongCat-2.0
ProviderMoonshot AI (China) Meituan (China)
ReleasedOctober 23, 2026 July 5, 2026
Context window1M tokens (~1,573 pages) 1M (~1,500 pages)
Price (in/out)$2/$10 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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 is the newer of the two.

Terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis

Kimi K3.1 Pro

LongCat-2.0 is comparatively weak here — headline scores are vendor-reported on SWE-Bench Pro, not the Verified set

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 K3.1 Pro lists artificial Analysis Intelligence Index of 55, second only to Claude Opus 5.5 (58) among the models AI Weekly lists among its strengths; LongCat-2.0 does not.

Near-frontier agentic coding — topped OpenRouter anonymously as 'Owl Alpha' for two months

LongCat-2.0

Open weights make this possible at all — Kimi K3.1 Pro is API-only, so it cannot leave the vendor's servers.

Massive native 1M context at near-linear cost via sparse attention

LongCat-2.0

A trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips — and its weights are open while Kimi K3.1 Pro is API-only.

Fully MIT-licensed 1.6T-parameter mixture-of-experts (about 48B active)

LongCat-2.0

Kimi K3.1 Pro is comparatively weak here — self-hosting is impractical - about 1.4 TB of raw weights even at 4-bit

Lowest cost at scale

LongCat-2.0

Its weights are open, so at volume you pay for your own hardware instead of Kimi K3.1 Pro's $2/$10 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

→ LongCat-2.0

At Open weight (self-host / free) 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

→ LongCat-2.0

Open weights let you run it on your own hardware; Kimi K3.1 Pro is API-only.

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

It is specifically built for that.

Anyone whose priority is near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months

→ LongCat-2.0

That is its strongest area.

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 are real: 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.

LongCat-2.0: where it fits

A trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips. Released July 5, 2026 by Meituan, it is built for near-frontier agentic coding — topped OpenRouter anonymously as 'Owl Alpha' for two months, massive native 1M context at near-linear cost via sparse attention, fully MIT-licensed 1.6T-parameter mixture-of-experts (about 48B active), and trained end to end on domestic Chinese chips, independent of Nvidia hardware.

Its trade-offs: a 1.6T model is extremely expensive to self-host, so most use leans on the China-hosted API, and headline scores are vendor-reported on SWE-Bench Pro, not the Verified set. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

The defining split here is open vs. closed. LongCat-2.0 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Kimi K3.1 Pro gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Kimi K3.1 Pro and LongCat-2.0 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 K3.1 Pro or LongCat-2.0 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 K3.1 Pro leans toward sparse moe with 2.8t total and about 104b active parameters, post-trained from the kimi k3 base while LongCat-2.0 leans toward near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Kimi K3.1 Pro or LongCat-2.0?

LongCat-2.0 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?

Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Kimi K3.1 Pro and LongCat-2.0 together?

Yes — a multi-model platform like LumiChats gives you Kimi K3.1 Pro, LongCat-2.0 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 K3.1 Pro or LongCat-2.0?

Kimi K3.1 Pro — released October 23, 2026, about 4 months after LongCat-2.0.

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.