Kimi K3: Complete Guide to Moonshot's 2.8T Model (2026)

Kimi K3 is the newest flagship AI model from Moonshot AI, officially launched on July 16, 2026. It is the largest open-weight model ever released — a 2.8-trillion-parameter mixture-of-experts system with a 1-million-token context window, native image and video understanding, and benchmark scores that put it within striking distance of GPT-5.6 Sol and Claude Fable 5 at roughly half the cost per task.

This is the hub guide. Each section below gives you the essentials, then links to a dedicated deep-dive if you want more detail on that topic.

Many people search for it as “Kimi 3.0” — the official name is Kimi K3, following Kimi K2 from 2025.

What is Kimi K3?

Kimi K3 is a frontier-class large language model built by Moonshot AI, the Beijing-based lab behind the Kimi assistant. Where Kimi K2 was a strong open-weight model with a 1T-parameter architecture, K3 is a generational leap: nearly 3× the parameters, 4× the context window, and two brand-new architectural techniques — Kimi Delta Attention (KDA) and Attention Residuals — that make it dramatically faster on long contexts.

Three things define K3:

1. Scale with efficiency. 2.8 trillion total parameters, but only 16 of its 896 experts are active per token. You get frontier intelligence without frontier-level inference cost.
2. A 1M-token context window. K3 can hold entire codebases, books, or hours of video transcripts in a single prompt — and its KDA architecture makes long-context decoding up to 6.3× faster than K2.
3. Agentic strength. K3 is built for multi-step, tool-using work: coding agents, browser automation, spreadsheets, and deep research. It ranks #1 on 4 of 8 real-world agentic benchmarks in Moonshot’s launch suite.

Independent testers at Artificial Analysis place K3 at #4 out of 189 AI models (score 57), ahead of Claude Opus 4.8 and GPT-5.5 — the highest rank ever achieved by an open-weight model.

Key specifications at a glance

Spec	Kimi K3
Total parameters	2.8T
Architecture	KDA + Attention Residuals + Stable LatentMoE
Experts	896 (16 active per token)
Context window	1,048,576 tokens (1M)
Vision / video input	Native
Long-context decode	Up to 6.3× faster than K2
Scaling efficiency	~2.5× better than K2
Weights license	Modified MIT (releases July 27)

For the full breakdown of every spec — including what KDA and Attention Residuals actually do, and why the expert count matters — read the dedicated guide: Kimi K3 Specifications Explained.

Benchmark performance

K3’s launch benchmarks show it beating or matching the best closed models on real-world agentic tasks:

Benchmark	Kimi K3	Best competitor	Result
Program Bench	77.8	GPT-5.6 Sol (77.6)	K3 #1
SWE Marathon	42.0	Claude Opus 4.8 (40.0)	K3 #1
BrowseComp	91.2	GPT-5.6 Sol (90.4)	K3 #1
SpreadsheetBench 2	34.8	Claude Fable 5 (34.7)	K3 #1
Automation Bench	30.8	GPT-5.6 Sol (29.7)	K3 #1
Terminal-Bench 2.1	88.3	GPT-5.6 Sol (88.8)	K3 #2 by 0.5

K3 is also #1 on the Frontend Code Arena leaderboard (K2.6 was #18). Moonshot itself is transparent that K3 still trails GPT-5.6 Sol and Claude Fable 5 overall — but it is the only open model anywhere near them, and it costs far less per completed task.

For the full head-to-head — every benchmark, cost per task, and which model wins for which workload — read Kimi K3 vs GPT-5.6 vs Claude Fable 5 vs Opus 4.8.

Pricing: how much does Kimi K3 cost?

K3’s API pricing is aggressive — Sonnet-tier prices for near-frontier intelligence:

Kimi K3 API	Per 1M tokens
Cache-hit input	$0.30
Cache-miss input	$3.00
Output	$15.00
Avg. cost per benchmark task	$0.94

Thanks to Moonshot’s Mooncake disaggregated inference (with >90% cache-hit rates in coding workloads), K3 works out to roughly 50% cheaper per completed task than Claude Opus 4.8 or GPT-5.5, and about 3× cheaper than Claude Fable 5 ($2.75/task).

If you just want to use K3 rather than build on it, it’s free in the Kimi app — no credit card required. Heavy launch traffic means free tiers can queue; membership skips the line.

How to access Kimi K3

There are four official ways to use K3 today:

1. Kimi app & kimi.com — free chat on iOS, Android, HarmonyOS, or the web. The fastest way to try it.
2. Kimi Work — the desktop app (Windows / Apple silicon, v3.1.0+) for deep research, widgets and dashboards. This is the answer if you’re looking to download Kimi K3 for PC.
3. Kimi Code — terminal + IDE agent. Run it and switch to K3 with the /model command.
4. Kimi API — an OpenAI-compatible endpoint at platform.moonshot.ai. Create an API key, select kimi-k3, and you’re running.

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_MOONSHOT_API_KEY",
    base_url="https://api.moonshot.ai/v1",
)

resp = client.chat.completions.create(
    model="kimi-k3",
    messages=[{"role": "user", "content": "Refactor this repo"}],
    reasoning_effort="max",  # default at launch
)

One warning: because of the launch hype, clone and phishing sites have appeared imitating Kimi. Before entering any credentials, read Kimi AI Official Website: How to Find the Real One.

Kimi K3 vs Kimi K2

If you used K2, here’s the short version: K3 is not an update — it’s a new generation.

Spec	Kimi K2	Kimi K3
Total parameters	1.0T	2.8T
Architecture	MLA MoE	KDA + AttnRes + Stable LatentMoE
Experts	384	896 (16 active / token)
Context window	256K tokens	1,048,576 tokens
Vision / video input	—	Native
Frontend Code Arena	#18 (K2.6)	#1

The full analysis — including which model still makes sense for self-hosters and fine-tuners — is in Kimi K3 vs Kimi K2: Full Comparison.

Release timeline

• July 16, 2026 — Kimi K3 announced and live in the Kimi app, API, Kimi Work and Kimi Code.
• July 27, 2026 — open weights scheduled for release under a Modified MIT license.

For the story of how the launch unfolded (and how the pre-launch rumors held up), see Kimi K3 Release Date & Rumor Recap.

Limitations to know about

No model is magic, and K3 has real trade-offs:

• Not #1 overall. On independent aggregate testing it sits behind GPT-5.6 Sol and Claude Fable 5. If you need the absolute top score regardless of cost, those still win.
• Self-hosting is heavy. 2.8T parameters means the open weights will demand serious multi-GPU infrastructure. Most people should use the API or app.
• Free-tier queues. Launch traffic means the free tier in the Kimi app can be slow at peak times.
• Reasoning effort is maxed by default at launch in the API — great for quality, but watch latency and token spend on simple tasks.

FAQ

Is Kimi K3 free? Yes — you can chat with K3 free in the Kimi app and on kimi.com. The API is paid, and membership plans skip free-tier queues.

Is Kimi K3 open source? The weights release on July 27, 2026 under a Modified MIT license — open-weight, with some usage conditions. Check the license before commercial deployment.

What’s the difference between “Kimi K3” and “Kimi 3.0”? Nothing — they’re the same model. “Kimi K3” is the official name; “Kimi 3.0” is just how many people search for it.

Is Kimi K3 better than GPT-5? On several real-world agentic benchmarks (Program Bench, SWE Marathon, BrowseComp, SpreadsheetBench 2, Automation Bench), yes — K3 scores #1. On overall aggregate intelligence rankings, GPT-5.6 Sol and Claude Fable 5 still lead, but K3 costs roughly half as much per task.

How do I get free Kimi K3 credits? Moonshot’s referral program gives both the inviter and the new user bonus membership credits. Sign up through an invite link and you can get up to a full year of membership credits free.

The bottom line

Kimi K3 is the most capable open-weight model ever released, and the first one that genuinely pressures the closed frontier on real-world agentic work — at half the price. Whether you’re a developer looking at the API, a researcher waiting for the July 27 weights, or a curious user who just wants to try it in the app, the guides linked above will take you deeper on every topic.