Take that article and increase it by the gemm gains.
At the end of the day, MI300x is outperforming an H100.
More importantly is that you need 2xH100 to do 70B and only 1xMI300x.
Take that article and increase it by the gemm gains.
At the end of the day, MI300x is outperforming an H100.
More importantly is that you need 2xH100 to do 70B and only 1xMI300x.
llama3-70b throughput:
Chips and Cheese: 4800 tok/sec (?!)
This article: 849 tok/sec (fastest optimized)
Mixtral 7B latency:
Chips and cheese: 1.17s
This article: 2.04s (fastest unoptimised) / 0.81 (fastest optimised)
And then finally comparing mixtral 8x7b to the Reddit article using batch size 1...
Reddit: 157 tok/sec
This article: 165 tok/sec (optimized) or 141 tok/sec (unoptimised)I still can't explain throughput differences though
The video shows that the optimized run with Llama-2 70B gives 314 tokens/s for a bs=1 with 256 prompt + 256 generation. The Groq system is also a bs=1 apparatus and gets you around 300 tokens/s. Wild!
[1] https://wow.groq.com/groq-sets-new-large-language-model-perf...
Groq does not talk about how many cards they need to get those results. Someone replied to me with this comment [1] a while ago...
[0] https://www.reddit.com/r/AMD_MI300/comments/1dqhrbn/comment/...
So, that's like $10M+ for serving bs=1 Llama-2 70B vs whatever a single MI300X costs?
300 tokens/s with bs=1 for a llama-2 70B on a single card is no joke.
All open source by the way.