LOADING DATASHEET
LOADING DATASHEET
by Moonshot
RANKED #70 OF 228 ASSISTANTS · OVERALL #116 OF 6,618 · VIBE SCORE 6.2 · 200 VOICES
Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...
28 mentions
16 mentions
26 weeks · 301 voices
QUIETLY DEGRADING
Recent vibe and chatter are both sliding.
Open weights. You can use a hosted service, or download it and run it yourself, free.
Open weights: download Kimi K2.6 once and it's yours. No subscription, no rate limits, works offline.
1T parameters (32B active MoE), a native INT4 file is about 594 GB, dynamic 2-bit is about 350 GB
Custom PC with AMD Ryzen 9 7900X, 512 GB DDR5 RAM, and RTX 3
512 GB SYSTEM RAM + 12 GB VRAM
~$2,200 BUILTExtreme offloading; model is too massive for single consumer GPUs, runs dynamic 2-bit or Q2 via CPU/RAM at very slow spe
Apple Mac Studio M3 Ultra with 512 GB Unified Memory
512 GB UNIFIED MEMORY
~$6,999 NEWQuantized 2.5-bit to 3-bit MLX or GGUF quants, comfortable local response at ~8-14 tok/s with moderate context
Dedicated Enterprise Server with 8x NVIDIA RTX 6000 Ada 48GB
384 GB TO 512 GB VRAM
~$55,000 WORKSTATIONNative INT4/FP8 weights at full speed across 8 GPUs, ~35-50 tok/s with full 256k context
The three cards above are researched picks. Search the machine you actually have — we only say yes if it should reply at a usable speed, not just load the weights and crawl.
HARDWARE PICKS & PRICES ARE RESEARCHED FROM THE LIVE WEB AND REFRESHED AUTOMATICALLY. TREAT THEM AS BALLPARK, NOT GOSPEL.
Everyday jobs on each of those rigs: how long Kimi K2.6 takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMCustom PC with AMD Ryzen 9 7900X, 512 GB DDR5 RAM, and RTX 3 | SWEET SPOTApple Mac Studio M3 Ultra with 512 GB Unified Memory | FULL POWERDedicated Enterprise Server with 8x NVIDIA RTX 6000 Ada 48GB |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | —★★★★★ | ~45 S★★★★★ | ~12 S★★★★★ |
| Summarize a documenta long report boiled down to the points that matter | —★★★★★ | ~2.3 MIN★★★★★ | ~35 S★★★★★ |
| Build a websitea small landing page, markup and styles together | —★★★★★ | ~12 MIN★★★★★ | ~3.1 MIN★★★★★ |
| Build a backendan API with routes, storage and tests | —★★★★★ | ~38 MIN★★★★★ | ~9.8 MIN★★★★★ |
| Build a gamea playable browser game in one file | —★★★★★ | ~23 MIN★★★★★ | ~5.9 MIN★★★★★ |
STARS ARE THE COMMUNITY SCORE FOR THAT KIND OF WORK, DOCKED FOR HOW SQUASHED THE WEIGHTS GET AT EACH TIER. A DASH MEANS NO SPEED WAS RESEARCHED FOR THAT RIG. TIMES ARE COMPUTED FROM RESEARCHED SPEEDS. BALLPARK, NOT GOSPEL.
People are mostly happy with Kimi K2.6. Biggest praise: help with code. Biggest gripe: saying no too much.
167 POSTS · 33 COMMENTS · HACKER NEWS · BLUESKY · GITHUB · REDDIT · X · DEV FORUMS · LEMMY · DEV.TO · BLOG
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“The tech report goes into great detail, including the architectural changes used to achieve better and cheaper long-context performance.”
Other models the crowd has fully reviewed, starting with multimodal models like this one.
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Made the switch to DeepSeek and here are my thoughts as a long time Claude user (spoiler: it's great)
Cerebras is running a trillion parameter model (Kimi K2.6) at 1000 tokens/s
First 1$ spent on deepseek
Made this comparison table to show why you don't have to cancel GHCP.