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Ember-1 is pitched as Kimi K3 post-trained for 40% more concise reasoning

The person introducing Ember-1 says their research team made it and claims it keeps the same quality as Kimi K3 while being 40% faster and cheaper.

Sebastian RaschkaSR
elvisEL
Sonya Huang 🐥SH
7 Sources, 13d ago, first seen 13d ago

TLDR

The person introducing Ember-1 says their research team post-trained Kimi K3 to be 40% more concise in its reasoning. They claim Ember-1 keeps the same quality while being 40% faster and cheaper.

Combined views

107.4K

7 Sources, first seen 13d ago

831 likes80 comments419 saves70 reposts

Combined views

107.4K

7 Sources, first seen 13d ago

831 likes80 comments419 saves70 reposts

Sentiment

Positive84.9%15.1%Negative

Summary

Many accounts welcomed Ember-1’s post-training for delivering 40% more concise reasoning at the same quality and lower inference cost on Kimi K3, while some doubted the gains would hold beyond the reported benchmarks.

Based on 47 sentiment-bearing replies from 41 accounts across 4 conversations.

Featured Source

Sentiment

Positive84.9%15.1%Negative

Summary

Many accounts welcomed Ember-1’s post-training for delivering 40% more concise reasoning at the same quality and lower inference cost on Kimi K3, while some doubted the gains would hold beyond the reported benchmarks.

Based on 47 sentiment-bearing replies from 41 accounts across 4 conversations.

Related

Fireworks AI Releases Kimi K3 Open Frontier Model

Hosts open-weights frontier model for inference and training at lower cost.

7 Sources

Dmytro Dzhulgakov@dzhulgakovEmber-1 is hot on HN, our research team cooked it’s Kimi K3 post trained to be 40% more concise in reasoning same quality, 40% faster and cheaper13d
Sonya Huang 🐥@sonyatweetybirdthe inference platforms are doing hardcore work, post-training open weight models to solve customer problems: @FireworksAI_HQ ember-1 @fal H3 max more to come;) makes total sense considering their position in the ecosystem, technical expertise, and economies of scale13d
Sebastian Raschka@rasbtA little Ember-1 tl;dr. Seems like a great model! (Was recently asked on a podcast, given $ xx million, what's the best way to develop a frontier LLM today? My recommendation was: start with an existing one and spend that budget on post-training. Great example here.)13d
elvis@omarsar0This is a bigger deal than it seems. I like this push on the Pareto frontier to squeeze as much as you can out of your tokens. Feels underexplored. All labs are quick to launch models, so certain aspects just aren't optimized. These are just a few of the great things you can start doing with frontier open models. Ember-1 produces shorter reasoning traces (40% fewer tokens) without sacrificing performance.13d
Lin Qiao@lqiaoRT @dzhulgakov: Ember-1 is hot on HN, our research team cooked it’s Kimi K3 post trained to be 40% more concise in reasoning same quality…12d
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    Ember-1Fireworks AI

    7 Sources

    Dmytro Dzhulgakov@dzhulgakovEmber-1 is hot on HN, our research team cooked it’s Kimi K3 post trained to be 40% more concise in reasoning same quality, 40% faster and cheaper13d
    Sonya Huang 🐥@sonyatweetybirdthe inference platforms are doing hardcore work, post-training open weight models to solve customer problems: @FireworksAI_HQ ember-1 @fal H3 max more to come;) makes total sense considering their position in the ecosystem, technical expertise, and economies of scale13d
    Sebastian Raschka@rasbtA little Ember-1 tl;dr. Seems like a great model! (Was recently asked on a podcast, given $ xx million, what's the best way to develop a frontier LLM today? My recommendation was: start with an existing one and spend that budget on post-training. Great example here.)13d
    elvis@omarsar0This is a bigger deal than it seems. I like this push on the Pareto frontier to squeeze as much as you can out of your tokens. Feels underexplored. All labs are quick to launch models, so certain aspects just aren't optimized. These are just a few of the great things you can start doing with frontier open models. Ember-1 produces shorter reasoning traces (40% fewer tokens) without sacrificing performance.13d
    Lin Qiao@lqiaoRT @dzhulgakov: Ember-1 is hot on HN, our research team cooked it’s Kimi K3 post trained to be 40% more concise in reasoning same quality…12d
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