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English(EN) Fresh open weights on the leaderboard: LFM3-1.7B (Liquid) packs 262k context at $0.08/$0.2 per 1M tokens – rare efficiency for its size. https:// olud.ai/latest

LFM3-1.7B (Liquid) 模型发布,拥有 262k 上下文和高效率

LFM3-1.7B 模型,又称 Liquid,已以开放权重形式发布。该模型拥有 262,000 个 token 的上下文窗口,定价具有竞争力,每百万 token 仅需 $0.08/$0.2。在其模型规模中,其效率尤为罕见。 AI

影响 提供了一个新的、高效的开放权重模型,具有大型上下文窗口,可能影响先进 LLM 功能的成本和可访问性。

排序理由 发布了一个具有显著技术规格的开放权重模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — mastodon.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LFM3-1.7B (Liquid) 模型发布,拥有 262k 上下文和高效率

本文如何被排名

Signal score
3 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
发布了一个具有显著技术规格的开放权重模型。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · opensourceaitech ·

    排行榜上的新开源模型:LFM3-1.7B (Liquid) 拥有 262k 上下文,每 100 万个 token 仅需 0.08 美元/0.2 美元 – 在同等规模下效率罕见。https:// olud.ai/latest

    Fresh open weights on the leaderboard: LFM3-1.7B (Liquid) packs 262k context at $0.08/$0.2 per 1M tokens – rare efficiency for its size. https:// olud.ai/latest.html # AI # LLM # OpenSource