I don't think you can buy a single "MI300X" unit, right? Only the box with x8 of these at a cost of ~250K EUR.
The MI350p exists and should run a decent quant (say, the ~96GB antirez mix) well, but you can get two rtx pro 6000s for one of these, or 8x (actually more) r9700 + probably the gear to run them, etc. Otherwise, you can probably buy one of these second hand from somewhere (SXM A100s are available that way) and run it in an adapter board.
DeepSeek V4 Flash on a Single AMD MI300X
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Re: DeepSeek V4 Flash on a Single AMD MI300X
#42Is their hardware programming interface reasonable for implementing inference of frontier models: no quantization, several tera params? BTW, how many many params open weight frontier models have? A few teras, 100s of teras?
Qwen3.8-Max: 2.4T
DeepSeek V4 Pro: 1.6T
DeepSeek V4 Flash: 284B
(all are total parameter counts, not active parameters)
Re: DeepSeek V4 Flash on a Single AMD MI300X
#43Earlier quoted context omitted.
At 830tok/s * 1 hour that's almost 3M tokens which is just $0.54 worth of tokens at Deepseeks current output price.
How is that economically viable? They are selling at a loss?
Re: DeepSeek V4 Flash on a Single AMD MI300X
#44Earlier quoted context omitted.
At 830tok/s * 1 hour that's almost 3M tokens which is just $0.54 worth of tokens at Deepseeks current output price.
How is that economically viable? They are selling at a loss?
Re: DeepSeek V4 Flash on a Single AMD MI300X
#45I don't think you can buy a single "MI300X" unit, right? Only the box with x8 of these at a cost of ~250K EUR.
Re: DeepSeek V4 Flash on a Single AMD MI300X
#46Unfortunately, the MI300X is an OAM module. The MI350P is the one you want: It's a PCIe card, but it has less memory: 144GB. Luckily, DeepSeek V4 Flash will run in 144GB too because it's 256 MoE exports are native MXFP4 quantized.
When they just loaded the weights alone, it was taking 156GB in vLLM. After warm-up and adding a KV cache pool, it took over 200GB.
And this implementation is already cutting down the 1M token context window you would normally get.
Re: DeepSeek V4 Flash on a Single AMD MI300X
#47Earlier quoted context omitted.
Give it an AI-bubble pop and these will be flooding the market.
When is it popping? Is the AI bubble in the room with us now?
Re: DeepSeek V4 Flash on a Single AMD MI300X
#48Dumbed down quantization?
No. Full intended inference weights preserved, so far so good.
Slow performance?
No again. Looks like you could get over 150 tokens/second.
Give up context window size?
Yes. Original model is trained for and served at 1M, this is 256k. A very practical tradeoff though. Codex is in this range, and quality does start to drop off toward the full size.
Re: DeepSeek V4 Flash on a Single AMD MI300X
#49Earlier quoted context omitted.
How is that economically viable? They are selling at a loss?
Agentic workloads are somewhere around 1%/0.5%/98.5% input/output/cached tokens. Cached tokens are pretty much free for inference providers (if they implement sparse and compressed attention properly) and throughput for input tokens is much higher. Lets assume that you've got 2 million input tokens, 1 million output tokens and 98.5 million cached tokens to process. That would cost 2 * $0.14 + 1 * $0.28 + 98.5 * $0.00…
That's agentic feedback loops for training, right? Any more detail on this, such as how they actually tell whether that data is good or not? That seems like a very hard problem, and like the value of that data is low compared to just building their own, controlled RL gyms.
Re: DeepSeek V4 Flash on a Single AMD MI300X
#50we did some work on this for 2xMi300x (kindly referenced in the readme) https://blog.doubleword.ai/deepseek-v4-flash-mi300x. https://hotaisle.xyz/quick-start hotaisle is great for getting Mi300x to experiment with