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Comment by thesurlydev | Hacker News Reader

Can you share how you're running it?

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.

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!

https://github.com/MoonshotAI/kimi-cli

I like Kimi-cli but it does leak memory.

I was using it for multi-hour tasks scripted via an self-written orchestrator on a small VM and ended up switching away from it because it would run slower and slower over time.

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.

so there's a free plan at moonshot.ai that gives you some number of tokens without paying?

Where? https://www.kimi.com/code starts at $19/month, which is same as the big boys.

> 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.

[1] https://help.kagi.com/kagi/ai/assistant.html

Doesn't list Kimi 2.5 and seems to be chat-only, not API, correct?

> Doesn't list Kimi 2.5 and seems to be chat-only, not API, correct?

Yes, it is chat only, but that list is out of date - Kimi 2.5 (with or without reasoning) is available, as are ChatGPT 5.2, Gemini 3 Pro (Preview), etc

https://unsloth.ai/docs/models/kimi-k2.5

Requirements are listed.

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.

I'm running the Q4_K_M quant on a xeon with 7x A4000s and I'm getting about 8 tok/s with small context (16k). I need to do more tuning, I think I can get more out of it, but it's never gonna be fast on this suboptimal machine.

The pitiful state of GPUs. $10K for a sloth with no memory.

you can add 1 more GPU so you can take advantage of tensor parallel. I get the same speed with 5 3090's with most of the model on 2400mhz ddr4 ram, 8.5tk almost constant. I don't really do agents but chat, and it holds up to 64k.

That is a very good point and I would love to do it, but I built this machine in a desktop case and the motherboard has seven slots. I did a custom water cooling manifold just to make it work with all the cards.

I'm trying to figure out how to add another card on a riser hanging off a slimsas port, or maybe I could turn the bottom slot into two vertical slots.. the case (fractal meshify 2 xl) has room for a vertical mounted card that wouldn't interfere with the others, but I'd need to make a custom riser with two slots on it to make it work. I dunno, it's possible!

I also have an RTX Pro 6000 Blackwell and an RTX 5000 Ada.. I'd be better off pulling all the A7000s and throwing both of those cards in this machine, but then I wouldn't have anything for my desktop. Decisions, decisions!

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.

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.

You can plug another model in place of Anthropic ones in Claude Code.

That tends to work quite poorly because Claude Code does not use standard completions APIs. I tried it with Kimi, using litellm[proxy], and it failed in too many places.

It worked very well for me using qwen3 coder behind a litellm. Most other models just fail in weird ways though.

opencode is a good alternative that doesnt flake out in this way.

You can try Kimi's Anthropic-compatible API.

Just connect Claude Code to Kimi's API endpoint and everything works well

https://www.kimi.com/code/docs/en/more/third-party-agents.ht...

If you don't use Antrophic models there's no reason to use Claude Code at all. Opencode gives so much more choice.

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!

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