Kimi K3.1 Pro vs Llama 4 Maverick

Moonshot AI · China  |  Meta · US · 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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Choose Llama 4 Maverick if you need self-hosting or data privacy; Kimi K3.1 Pro if you want a managed API.

Kimi K3.1 Pro (Moonshot AI, China) and Llama 4 Maverick (Meta, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. 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 ProLlama 4 Maverick
ProviderMoonshot AI (China) Meta (US)
ReleasedOctober 23, 2026 April 2025
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, image, 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

Kimi K3.1 Pro lists terminal-Bench 4.0 of 65.7% (Moonshot) and 67% as measured by Artificial Analysis among its strengths; Llama 4 Maverick does not.

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; Llama 4 Maverick does not.

Open weights, 1M context

Llama 4 Maverick

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

Strong image + text understanding

Llama 4 Maverick

Meta's open-weight 1M-context multimodal model for self-hosted deployments — and its weights are open while Kimi K3.1 Pro is API-only.

Self-hostable

Llama 4 Maverick

Llama 4 Maverick lists self-hostable among its strengths; Kimi K3.1 Pro does not.

Lowest cost at scale

Llama 4 Maverick

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

→ Llama 4 Maverick

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

→ Llama 4 Maverick

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 open weights, 1m context

→ Llama 4 Maverick

That is its strongest area.

An enterprise with regional data-residency rules

→ Llama 4 Maverick or Kimi K3.1 Pro

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

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.

Llama 4 Maverick: where it fits

Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.

Its trade-offs: needs serious hardware to self-host, and trails closed frontier on reasoning. 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. Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Kimi K3.1 Pro or Llama 4 Maverick?

Llama 4 Maverick 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 Llama 4 Maverick together?

Yes — a multi-model platform like LumiChats gives you Kimi K3.1 Pro, Llama 4 Maverick 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 Llama 4 Maverick?

Kimi K3.1 Pro — released October 23, 2026, about 19 months after Llama 4 Maverick.

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.