Kimi-K3
Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.
Aggregates the rapidly growing field of AI for chip design with over 300 papers across 18 categories, providing a structured, up-to-date overview for researchers and practitioners.
A curated, community-maintained list of ML/LLM research & tools across the chip-design flow — from specification to silicon.
Artificial intelligence — large language models in particular — is reshaping how chips are designed, verified, and optimized. This list tracks research and open tools that apply ML/LLMs across the chip-design flow: specification and high-level synthesis, RTL generation, verification and debug, logic and physical synthesis, PPA optimization, analog and mixed-signal, FPGA, testing, and hardware security — plus the foundation models, benchmarks, datasets, techniques, and multi-agent frameworks that underpin them.
Inclusion does not imply endorsement; categories are best-effort and subjective — please open an issue or PR to correct them.
| 📦 Papers | 🗂️ Categories | 📅 Span | 📝 Listed entries |
|---|---|---|---|
| 329 | 18 | 2023–2026 | 403 |
📅 Papers by year
xychart-beta
title "Papers by year"
x-axis [2023, 2024, 2025, 2026]
y-axis "count" 0 --> 160
bar [15, 78, 149, 87]
🥧 Listed entries by category (top 9 + others)
pie title "Listed entries"
"RTL Generation" : 93
"Verification" : 62
"Multi-Agent" : 49
"Techniques" : 42
"Foundation" : 22
"Analog/MS" : 22
"Benchmarks" : 19
"Security" : 18
"HLS" : 18
"Others" : 58
A curated, community-maintained list of ML/LLM research and tools for integrated-circuit design — across the full flow.
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Kimi K3 is an open-weight, 2.8T-parameter native multimodal agentic model with a 1M-token context window, designed for frontier coding, knowledge work, and reasoning tasks.

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