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Moonshot AI releases Kimi K3 with 1M context, open weights, and competitive pricing

Moonshot AI has released Kimi K3, an open-weights model with approximately 2.8 trillion parameters and a 1 million token context window. The model achieved strong performance on benchmarks like Terminal-Bench 2.0, FrontierSWE, and GPQA Diamond. Notably, Kimi K3 has been ranked above Claude 3 Opus in Arena blind tests for text tasks and leads in front-end coding capabilities, surpassing all US frontier models. The release also features competitive pricing at $3/$15 per million tokens, positioning it as a frontier-level model despite its open-weight status. AI

IMPACT Sets a new bar for open-weight models, potentially accelerating adoption of large-context windows and challenging existing frontier models on price and performance.

RANK_REASON Frontier-lab model release with open weights and performance metrics. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Moonshot AI releases Kimi K3 with 1M context, open weights, and competitive pricing

How we ranked this

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0 / 100
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Significant
Frontier-lab model release with open weights and performance metrics. [lever_c_demoted from frontier_release: 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.
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model release, product
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
71 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Kimi K3 dropped tonight. Open weights, ~2.8T params, 1M context. The numbers: 88.3% Terminal-Bench 2.0, 81.2% FrontierSWE, 93.5% GPQA Diamond. Arena blind tests

    Kimi K3 dropped tonight. Open weights, ~2.8T params, 1M context. The numbers: 88.3% Terminal-Bench 2.0, 81.2% FrontierSWE, 93.5% GPQA Diamond. Arena blind tests rank it above Opus 4.8 on text — and first for front-end coding, ahead of every US frontier model. The real story is th…