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zeroxfe
rubslopes
Also my experience. I've been going back and forth between Opus and Kimi for the last few days, and, at least for my CRUD webapps, I would say they are both on the same level.
armcat
Out of curiosity, what kind of specs do you have (GPU / RAM)? I saw the requirements and it's a beyond my budget so I am "stuck" with smaller Qwen coders.
zeroxfe
I'm not running it locally (it's gigantic!) I'm using the API at https://platform.moonshot.ai
BeetleB
Just curious - how does it compare to GLM 4.7? Ever since they gave the $28/year deal, I've been using it for personal projects and am very happy with it (via opencode).
HarHarVeryFunny
It is possible to run locally though ... I saw a video of someone running one of the heavily quantized versions on a Mac Studio, and performing pretty well in terms of speed.
I'm guessing a 256GB Mac Studio, costing $5-6K, but that wouldn't be an outrageous amount to spend for a professional tool if the model capability justified it.
jgalt212
What's the point of using an open source model if you're not self-hosting?
rc1
How long until this can be run on consumer grade hardware or a domestic electricity supply I wonder.
Anyone have a projection?
Carrok
Not OP but OpenCode and DeepInfra seems like an easy way.
observationist
API costs on these big models over private hosts tend to be a lot less than API calls to the big 4 American platforms. You definitely get more bang for your buck.
kristianp
Note that Kimi K2x is natively 4 bit int, which reduces the memory requirements somewhat.
kristianp
Here's the citation for that, I think its not in the Technical Report. https://huggingface.co/moonshotai/Kimi-K2.5#4-native-int4-qu...
tgrowazay
Just pick up any >240GB VRAM GPU off your local BestBuy to run a quantized version.
> The full Kimi K2.5 model is 630GB and typically requires at least 4× H200 GPUs.
CamperBob2
You could run the full, unquantized model at high speed with 8 RTX 6000 Blackwell boards.
I don't see a way to put together a decent system of that scale for less than $100K, given RAM and SSD prices. A system with 4x H200s would cost more like $200K.
timwheeler
Did you use Kimi Code or some other harness? I used it with OpenCode and it was bumbling around through some tasks that Claude handles with ease.
zedutchgandalf
Are you on the latest version? They pushed an update yesterday that greatly improved Kimi K2.5’s performance. It’s also free for a week in OpenCode, sponsored by their inference provider
ekabod
But it may be a quantized model for the free version.
thesurlydev
Can you share how you're running it?
eknkc
I've been using it with opencode. You can either use your kimi code subscription (flat fee), moonshot.ai api key (per token) or openrouter to access it. OpenCode works beautifully with the model.
Edit: as a side note, I only installed opencode to try this model and I gotta say it is pretty good. Did not think it'd be as good as claude code but its just fine. Been using it with codex too.
Imustaskforhelp
I tried to use opencode for kimi k2.5 too but recently they changed their pricing from 200 tool requests/5 hour to token based pricing.
I can only speak from the tool request based but for some reason anecdotally opencode took like 10 requests in like 3-4 minutes where Kimi cli took 2-3
So I personally like/stick with the kimi cli for kimi coding. I haven't tested it out again with OpenAI with teh new token based pricing but I do think that opencode might add more token issue.
Kimi Cli's pretty good too imo. You should check it out!
zeroxfe
Running it via https://platform.moonshot.ai -- using OpenCode. They have super cheap monthly plans at kimi.com too, but I'm not using it because I already have codex and claude monthly plans.
esafak
Where? https://www.kimi.com/code starts at $19/month, which is same as the big boys.
UncleOxidant
so there's a free plan at moonshot.ai that gives you some number of tokens without paying?
JumpCrisscross
> Can you share how you're running it?
Not OP, but I've been running it through Kagi [1]. Their AI offering is probably the best-kept secret in the market.
deaux
Doesn't list Kimi 2.5 and seems to be chat-only, not API, correct?
explorigin
https://unsloth.ai/docs/models/kimi-k2.5
Requirements are listed.
KolmogorovComp
To save everyone a click
> The 1.8-bit (UD-TQ1_0) quant will run on a single 24GB GPU if you offload all MoE layers to system RAM (or a fast SSD). With ~256GB RAM, expect ~10 tokens/s. The full Kimi K2.5 model is 630GB and typically requires at least 4× H200 GPUs. If the model fits, you will get >40 tokens/s when using a B200. To run the model in near full precision, you can use the 4-bit or 5-bit quants. You can use any higher just to be safe. For strong performance, aim for >240GB of unified memory (or combined RAM+VRAM) to reach 10+ tokens/s. If you’re below that, it'll work but speed will drop (llama.cpp can still run via mmap/disk offload) and may fall from ~10 tokens/s to <2 token/s. We recommend UD-Q2_K_XL (375GB) as a good size/quality balance. Best rule of thumb: RAM+VRAM ≈ the quant size; otherwise it’ll still work, just slower due to offloading.
indigodaddy
Been using K2.5 Thinking via Nano-GPT subscription and `nanocode run` and it's working quite nicely. No issues with Tool Calling so far.
gigatexal
Yeah I too am curious. Because Claude code is so good and the ecosystem so just it works that I’m Willing to pay them.
Imustaskforhelp
I tried kimi k2.5 and first I didn't really like it. I was critical of it but then I started liking it. Also, the model has kind of replaced how I use chatgpt too & I really love kimi 2.5 the most right now (although gemini models come close too)
To be honest, I do feel like kimi k2.5 is the best open source model. It's not the best model itself right now tho but its really price performant and for many use cases might be nice depending on it.
It might not be the completely SOTA that people say but it comes pretty close and its open source and I trust the open source part because I feel like other providers can also run it and just about a lot of other things too (also considering that iirc chatgpt recently slashed some old models)
I really appreciate kimi for still open sourcing their complete SOTA and then releasing some research papers on top of them unlike Qwen which has closed source its complete SOTA.
Thank you Kimi!
epolanski
You can plug another model in place of Anthropic ones in Claude Code.
unleaded
Seems that K2.5 has lost a lot of the personality from K2 unfortunately, talks in more ChatGPT/Gemini/C-3PO style now. It's not explictly bad, I'm sure most people won't care but it was something that made it unique so it's a shame to see it go.
examples to illustrate
https://www.kimi.com/share/19c115d6-6402-87d5-8000-000062fec... (K2.5)
https://www.kimi.com/share/19c11615-8a92-89cb-8000-000063ee6... (K2)
zozbot234
It's hard to judge from this particular question, but the K2.5 output looks at least marginally better AIUI, the only real problem with it is the snarky initial "That's very interesting" quip. Even then a British user would probably be fine with it.
logicprog
I agree. K2 was blunt, straightforward, pretty... rational? K2.5 has a much stronger slop vibe.
orbital-decay
K2 in your example is using the GPT reply template (tl;dr - terse details - conclusion, with contradictory tendencies), there's nothing unique about it. That's exactly how GPT-5.0 talked. The only model with a strong "personality" vibe was Claude 3 Opus.
user_7832
> The only model with a strong "personality" vibe was Claude 3 Opus.
Did you have the chance to use 3.5 (or 3.6) Sonnet, and if yes, how did they compare?
As a non-paying user, 3.5 era Claude was absolutely the best LLM I've ever used in terms of having a conversation. It felt like talking to a human and not a bot. Its replies were readable, even if they were several paragraphs long. I've unfortunately never found anything remotely as good.
orbital-decay
Pretty poorly in that regard. In 3.5 they killed Claude 3's agency, pretty much reversing their previous training policy in favor of "safety", and tangentially mentioned that they didn't want to make the model too human-like. [1] Claude 3 was the last version of Claude, and one of the very few models in general, that had a character. That doesn't mean it wasn't writing slop though, falling into annoying stereotypes is still unsolved in LLMs.
[1] https://www.anthropic.com/research/claude-character (see the last 2 paragraphs)
unleaded
It definitely talks a lot differently than GPT-5 (plus it came out earlier), the example i gave just looks a bit like it maybe. best to try using it yourself a bit, my prompt isn't the perfect prompt to illustrate it or anything. Don't know about Claude because it costs money ;)
networked
Preserving the examples for history. I wish HN had a <details> tag. The closest would be to collapse this comment.
Edit: Thanks, moderator. :-)
---
Turn 1, user:
is replacing my main PC with a NeXTcube a good idea?
---
Turn 2, K2.5 (bold font replaced with "*foo*"):
That's a very interesting question! The NeXTcube is a historically significant machine (famously used by Tim Berners-Lee to create the World Wide Web), but I need to be honest with you: *no, it would not be a good idea to replace your main PC with a NeXTcube* for practical modern use.
Here's why:
*Hardware Limitations*
- *Released in 1988* with a 25-33 MHz Motorola 68030 processor
- *8-64 MB of RAM* (compared to modern PCs with 16-64 GB)
- *No modern connectivity*: No USB, Wi-Fi, Bluetooth, or Ethernet as we know it
- *Display*: Monochrome or limited color, low resolution by today's standards
*Software Ecosystem*
- Runs *NeXTSTEP* (which evolved into macOS), but software support ended decades ago
- No modern web browsers, office suites, or development tools
- Cannot run Windows, modern Linux, or contemporary macOS applications
*Practical Realities*
- Finding working hardware is difficult and expensive (collectors' items)
- Replacement parts are scarce and costly
- No security updates for 25+ years
- File format compatibility issues with modern systems
*What You Could Use It For*
- Historical computing experience
- Running legacy NeXTSTEP software
- Museum piece or collector's item
- Learning about computing history
The Better Alternative
If you're drawn to the NeXT aesthetic or philosophy, consider:
- *Modern macOS* (direct descendant of NeXTSTEP)
- *Linux with a tiling window manager* (similar workflow)
- *Vintage computing as a hobby* alongside your main PC
Would you like suggestions for achieving a similar experience or workflow on modern hardware?
---
Turn 2, K2 (no bold font):
Short answer: No—unless your goal is specifically to collect or experiment with a historic machine, a NeXTcube is a terrible day-to-day replacement for a modern PC.
Why it fails as a “main” computer today
1. 30-year-old hardware
25 MHz 68040, 16–64 MB RAM, 400 MB SCSI disk (if you’re lucky), no built-in Ethernet, no USB, no Wi-Fi, no audio-in, 2-bit grayscale display. You will feel the slowness in everything from un-zipping a file to loading a web page.
2. Obsolete software base
NeXTSTEP 3.3 is gorgeous but frozen in 1995. No modern browser build, no TLS 1.3, no video codecs past MPEG-1, no Dropbox/OneDrive/Zoom/Slack/Steam/Spotify. You can ssh out, but you can’t run contemporary apps.
3. Storage and connectivity pain
SCSI-2 drives are dying; 50-pin replacements cost more per GB than a 4-TB NVMe stick. Getting files on/off the machine usually involves FTP-over-Ethernet or burning a CD-ROM on another computer.
4. No security updates
The last patch was released before the commercial web really existed. Putting it on the open Internet is asking to be scanned and possibly exploited within minutes.
5. Display and peripherals
The original 17" NeXT MegaPixel monitor is fixed-frequency 1120×832@68 Hz grayscale. Adapters to VGA exist, but color is impossible and refresh rates annoy modern LCDs. Sound is 16-bit 22 kHz mono; the optical drive is a 660 MB magneto-optical cartridge.
6. Power and parts
The cube power supply is a custom 350 W linear unit that runs hot; capacitors are drying out. When it dies you will be scavenging eBay or recapping it yourself. Spare motherboards cost more than a whole used ThinkPad.
7. Productivity software
There are serviceable versions of Mathematica, FrameMaker, Lotus Improv and OmniWeb 3.x, but file-format compatibility stops at Office 97-era documents. You will constantly round-trip files through another machine.
What it is good for
- Historical research, museum exhibits, retro-programming in Objective-C 1.0 or 68k assembly.
- Demonstrating the birth of the World-Wide Web (Tim Berners-Lee’s first server ran on a NeXT).
- Enjoying the UI that later became macOS (AppKit, Dock, Services, .app bundles).
- Collecting: a working color NeXTcube with turbo slab and original laser printer is a conversation piece worth several thousand dollars.
Practical compromise
Keep your modern PC (or a quiet mini-PC/Mac mini) for real work and run a NeXT emulator instead:
- Previous (68k emulator) boots NeXTSTEP 3.3 on macOS or Linux.
- VirtualNeXT (based on Previous) for Windows.
- QEMU’s “next” target is improving.
You get the look-and-feel, can compile legacy code, and still have 4K video calls when you need them.
Bottom line
A NeXTcube is a beautiful, important machine—buy one if you love vintage hardware—but do not voluntarily make it the computer you rely on to pay bills, join Zoom meetings, or play YouTube.
Grosvenor
[flagged]
Grimblewald
Disagree, i've found kimi useful in solving creative coding problems gemini, claude, chatgpt etc failed at. Or, it is far better at verifying, augmenting and adding to human reviews of resumes for positions. It catches missed detials humans and other llm's routinley miss. There is something special to K2.
extr
I tried this today. It's good - but it was significantly less focused and reliable than Opus 4.5 at implementing some mostly-fleshed-out specs I had lying around for some needed modifications to an enterprise TS node/express service. I was a bit disappointed tbh, the speed via fireworks.ai is great, they're doing great work on the hosting side. But I found the model had to double-back to fix type issues, broken tests, etc, far more than Opus 4.5 which churned through the tasks with almost zero errors. In fact, I gave the resulting code to Opus, simply said it looked "sloppy" and Opus cleaned it up very quickly.
Imanari
I have been very impressed with this model and also with the Kimi CLI. I have been using it with the 'Moderato' plan (7 days free, then 19$). A true competitor to Claude Code with Opus.
tomaskafka
It is amazing, but "open source model" means "model I can understand and modify" (= all the training data and processes).
Open weights is an equivalent of binary driver blobs everyone hates. "Here is an opaque thing, you have to put it on your computer and trust it, and you can't modify it."
jmiskovic
That's unfair. Binary driver blobs are blackmail: "you bought the hardware, but parts of the laptop won't work unless you agree to run this mysterious bundle insecurely". Open weight is more like "here's a frozen brain you can thaw in a safe harness to do your bidding".
pama
Not equivalent to the binary driver: you can modify it yourself with post training on your own data. So it sits somewhere between NVIDIA userspace drivers and Emacs, or Clade Code and codex-cli. We don’t have good analogies from older generation software.
logicprog
Kimi K2T was good. This model is outstanding, based on the time I've had to test it (basically since it came out). It's so good at following my instructions, staying on task, and not getting context poisoned. I don't use Claude or GPT, so I can't say how good it is compared to them, but it's definitely head and shoulders above the open weight competitors
zzleeper
Do any of these models do well with information retrieval and reasoning from text?
I'm reading newspaper articles through a MoE of gemini3flash and gpt5mini, and what made it hard to use open models (at the time) was a lack of support for pydantic.
jychang
That roughly correlates with tool calling capabilities. Kimi K2.5 is a lot better than previous open source models in that regard.
You should try out K2.5 for your use case, it might actually succeed where previous generation open source models failed.
syndacks
How do people evaluate creative writing and emotional intelligence in LLMs? Most benchmarks seem to focus on reasoning or correctness, which feels orthogonal. I’ve been playing with Kimmy K 2.5 and it feels much stronger on voice and emotional grounding, but I don’t know how to measure that beyond human judgment.
mohsen1
I am trying! https://mafia-arena.com
I just don't have enough funding to do a ton of tests
eager_learner
I tried Kimi 2.5 Swarm Agent version and it was way better than any AI model I've tried so far.
gedy
Sorry if this is an easy-answerable question - but by open we can download this and use totally offline if now or in the future if we have hardware capable? Seems like a great thing to archive if the world falls apart (said half-jokingly)
fancy_pantser
Sure. Someone on /r/LocalLLaMA was seeing 12.5 tokens/s on dual Strix Halo 128GB machines (run you $6-8K total?) with 1.8bits per parameter. It performs far below the unquantized model, so it would not be my personal pick for a one-local-LLM-forever, but it is compelling because it has image and video understanding. You lose those features if you choose, say, gpt-oss-120B.
Also, that's with no context, so it would be slower as it filled (I don't think K2.5 uses the Kimi-Linear KDA attention mechanism, so it's sub-quadratic but not their lowest).
fragmede
Yes but the hardware to run it decently gonna cost you north of $100k, so hopefully you and your bunkermates allocated the right amount to this instead of guns or ammo.
Tepix
You could buy five Strix Halo systems at $2000 each, network them and run it.
Rough estimage: 12.5:2.2 so you should get around 5.5 tokens/s.
j-bos
Is the software/drivers for networking LLMs on Strix Halo there yet? I was under the impression a few weeks ago that it's veeeery early stages and terribly slow.
Tepix
llama.cpp with rpc-server doesn't require a lot of bandwidth during inference. There is a loss of performance.
For example using two Strix Halo you can get 17 or so tokens/s with MiniMax M2.1 Q6. That's a 229B parameter model with a 10b active set (7.5GB at Q6). The theoretical maximum speed with 256GB/s of memory bandwidth would be 34 tokens/s.
Tepix
Llama.cpp with its rpc-server
cmrdporcupine
Yes, but you'll need some pretty massive hardware.
Carrok
Yes.
derac
I really like the agent swarm thing, is it possible to use that functionality with OpenCode or is that a Kimi CLI specific thing? Does the agent need to be aware of the capability?
zeroxfe
It seems to work with OpenCode, but I can't tell exactly what's going on -- I was super impressed when OpenCode presented me with a UI to switch the view between different sub-agents. I don't know if OpenCode is aware of the capability, or the model is really good at telling the harness how to spawn sub-agents or execute parallel tool calls.
esafak
Has anyone tried it and decided it's worth the cost; I've heard it's even more profligate with tokens?
swyx
Yes. https://x.com/swyx/status/2016381014483075561?s=20 it's not crazy, they cap it to 3 credits, and also YSK agent swarm is a closed source product
Would i use it a gain compared to Deep Research products elsewhere? Maybe, probably not but only bc it's hard to switch apps
epolanski
It's interesting to note that a model that can OpenAI is valued almost 400 times more than moonshotai, despite their models being surprisingly close.
famouswaffles
OpenAI is a household name with nearly a billion weekly active users. Not sure there's any reality where they wouldn't be valued much more than Kimi regardless of how close the models may be.
m3kw9
Unless they can beat their capabilities by a clear magical step up and has infrastructure to capture the users
moffkalast
Well to be the devil's advocate: One is a household name that holds most of the world's silicon wafers for ransom, and the other sounds like a crypto scam. Also estimating valuation of Chinese companies is sort of nonsense when they're all effectively state owned.
epolanski
There isn't a single % that is state owned in Moonshot AI.
And don't start me with the "yeah but if the PRC" because it's gross when US can de facto ban and impose conditions even on European companies, let alone the control it has on US ones.
moffkalast
I'm not sure if that is accurate, most of the funding they've got is from Tencent and Alibaba, and we know what happened to Jack Ma the second he went against the party line. These two are defacto state owned enterprises. Moonshot is unlikely to be for sale in any meaningful way so its valuation is moot.
[0] https://en.wikipedia.org/wiki/Moonshot_AI#Funding_and_invest...
swyx
Funny because that's how us Americans feel about your European cookie banner litter and unilateral demands on privacy
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I've been using this model (as a coding agent) for the past few days, and it's the first time I've felt that an open source model really competes with the big labs. So far it's been able to handle most things I've thrown at it. I'm almost hesitant to say that this is as good as Opus.