Kimi K3: A 2.8T Open Model That Can Code, Design Chips, and Edit Videos
On July 17, Moonshot AI unveiled Kimi K3 — the world's first open 3T-class model. With 2.8T parameters, KDA attention, and a 1M-token context window, it goes head-to-head with proprietary giants across coding and agentic benchmarks.
In the early hours of July 17, 2026, Moonshot AI dropped Kimi K3 — a 2.8-trillion-parameter model with a 1-million-token context window and native vision capabilities. It is the world's first open 3T-class model, and it doesn't just raise the bar for open-source AI — it puts it squarely in the ring with GPT-5.6 Sol and Claude Fable 5.
Elon Musk commented "Impressive." Arena AI's Frontend Code Arena ranked it #1 with a score of 1679.
More Than Just Big Numbers
The 2.8T parameters grab headlines — for nine of the past twelve months, Kimi models have set the upper bound of open-model sizes. But the real story is in the architecture.
K3 is built on two key innovations:
- Kimi Delta Attention (KDA): A hybrid linear attention mechanism that improves information flow across sequence length
- Attention Residuals (AttnRes): Selectively retrieves representations across depth rather than accumulating them uniformly
On the MoE side, K3 activates 16 of 896 experts, paired with a Stable LatentMoE framework for robust routing. According to Moonshot, these structural changes deliver an approximate 2.5× improvement in scaling efficiency over Kimi K2 — more intelligence per unit of compute.
Training incorporates quantization-aware techniques from the SFT stage onward, using MXFP4 weights with MXFP8 activations for broad hardware compatibility.
Coding: A New Benchmark for Long-Horizon Tasks
Coding is where Kimi K3 shines brightest.
| Benchmark | Kimi K3 | Claude Fable 5 | GPT-5.6 Sol |
|---|---|---|---|
| Terminal Bench 2.1 | 88.3 | 84.6 | 88.8 |
| SWE Marathon | 42.0 | 35.0 | 39.0 |
| Program Bench | 77.8 | 76.8 | 77.6 |
| DeepSWE | 67.5 | 70.0 | 73.0 |
| FrontierSWE | 81.2 | 86.6 | 71.3 |
K3 ranks first on SWE Marathon, the benchmark for ultra-long-horizon software engineering. On Terminal Bench 2.1 it edges past Fable 5. On real-world repository fixes (DeepSWE, FrontierSWE) it still trails the proprietary leaders — but the gap is narrowing fast.
The case studies are even more telling:
- Chip design: In a single 48-hour autonomous run, K3 designed, optimized, and verified a complete chip using open-source EDA tools on the Nangate 45nm library
- GPU compiler: Built MiniTriton from scratch — a compact Triton-like compiler with its own tile-level IR, optimization passes, and PTX codegen pipeline
- Research reproduction: Completed in ~2 hours what would take an experienced researcher 1-2 weeks — a computational astrophysics pipeline involving 20+ papers, 300+ equations of state, and 3,000+ lines of Python
Agents: Search, Operate, Edit
On agentic benchmarks, K3 holds its own:
| Benchmark | Kimi K3 | Claude Fable 5 | GPT-5.6 Sol |
|---|---|---|---|
| BrowseComp | 91.2 | 88.0 | 90.4 |
| Automation Bench | 30.8 | 29.1 | 29.7 |
| SpreadsheetBench 2 | 34.8 | 33.4 | 33.7 |
Its multimodal chops are equally impressive. K3 achieves true "vision in the loop" — iterating between code and live screenshots during game development and frontend work. Its own 36-second teaser video was autonomously edited from 56 source clips, handling clip selection, motion-matched cuts, and frame-accurate beat synchronization.
Open Source and Availability
Full model weights will be released on July 27, 2026. Until then, K3 is available through:
- Kimi.com and the Kimi mobile app (iOS / Android / HarmonyOS)
- Kimi Work desktop (Windows / Apple Silicon Mac)
- Kimi Code terminal tool
- Kimi API platform
API pricing: $0.30/MTok for cache-hit input, $3.00/MTok for cache-miss input, $15.00/MTok for output. Powered by Mooncake's disaggregated inference architecture, the official API achieves over 90% cache hit rate on coding workloads.
Limitations and Outlook
Moonshot is upfront about K3's weaknesses: sensitivity to thinking history (switching models mid-session degrades quality), occasional over-proactiveness on ambiguous tasks, and a still-noticeable experience gap versus Fable 5 and GPT-5.6 Sol.
But the signal is unmistakable. Anthropic's CEO once predicted that an open model matching Fable 5 would arrive in 6-12 months. Kimi K3 has arrived earlier — and harder — than anyone expected.