Dmitry [d9k]

Typescript Node.JS Fullstack Developer. Would love to develop educational games

[Tenkemo 🐾 Kickstarter Live! @TenkemoGame]

Making a cat for my game from scratch (no AI)
Follow my game on Kickstarter
https://t.co/jzGx2NXofk
#blender #gamedev #indiegame #Godot #kickstarter #cat

[Artificial Analysis @ArtificialAnlys]

KAT-Coder-Pro V2 uses significantly fewer tokens compared to models of similar intelligence as it is non-reasoning model. Using ~9M output tokens to run the Artificial Analysis Intelligence Index, KAT-Coder-Pro V2 is much more token efficient compared to DeepSeek V3.2 (~61M) and Qwen3.5 397B A17B (~86M)

[Artificial Analysis @ArtificialAnlys]

KwaiKAT has released KAT-Coder-Pro V2, a non-reasoning model that scores 44 on the Artificial Analysis Intelligence Index, an 8 point improvement from KAT-Coder-Pro V1

@KwaiAICoder has updated their flagship proprietary coding model with the release of KAT-Coder-Pro V2. KAT-Coder-Pro V2 achieves 44 on the Artificial Analysis Intelligence Index, matching Claude Sonnet 4.6 (non-reasoning) and trailing only Claude Opus 4.6 (non-reasoning, 46) among non-reasoning models. At ~9M output tokens, it is also more token efficient than Claude Opus 4.6 (~11M), Claude Sonnet 4.6 (~14M), and reasoning models with similar intelligence such as DeepSeek V3.2 (reasoning, ~61M) and Qwen3.5 397B A17B (reasoning, ~86M).

KAT-Coder-Pro V2 is a non-reasoning model, unlike all of the current frontier language models which ‘think’ before answering. Typically, reasoning variants score higher on the Intelligence Index than their non-reasoning counterparts, but consume more output tokens and are less suited to latency-sensitive workloads.

Key Highlights:

➤ 🧠 Higher overall intelligence, but regression in long context reasoning and knowledge recall: KAT-Coder-Pro V2 scores 44 on the Artificial Analysis Intelligence Index, an 8 point improvement from KAT-Coder-Pro V1 and matching Claude Sonnet 4.6 (non-reasoning, max effort). It performs well on tool use (90% on Tau2-Telecom), but regresses compared to KAT-Coder-Pro V1 on long-context reasoning and knowledge, falling 8 p.p. on AA-LCR (66%) and 17 p.p. on HLE (16%).

➤ 🤖 Agentic capability improvements: KAT-Coder-Pro V2 shows major improvements on our agentic evaluations. On Terminal-Bench Hard, it scores 49%, up 40 p.p. from KAT-Coder-Pro V1, making it the highest-scoring non-reasoning model, matching Claude Opus 4.6 (non-reasoning, 49%) and ahead of Claude Sonnet 4.6 (non-reasoning, 46%). KAT-Coder-Pro V2 also shows improvement in GDPval-AA, scoring 1123 (+304 Elo from V1), but still sits behind models such as DeepSeek V3.2 (1198) and Qwen3.5 397B A17B (1202).

➤ ⚙️ High token efficiency: KAT-Coder-Pro V2 is a non-reasoning model and uses fewer tokens than peers with similar intelligence. It uses 8.7M output tokens to run the Artificial Analysis Intelligence Index, below Claude Opus 4.6 (non-reasoning, ~11M) and Claude Sonnet 4.6 (non-reasoning, ~14M), though this is ~2x higher than its predecessor, KAT-Coder-Pro V1 (~4.5M). It also uses significantly fewer tokens than similarly intelligent reasoning models such as DeepSeek V3.2 (reasoning, ~61M) and Qwen3.5 397B A17B (reasoning, ~86M).

➤ $ Improved cost efficiency: KAT-Coder-Pro V2 costs $73 to run the Artificial Analysis Intelligence Index, down from $76 for V1, as it uses fewer input tokens by requiring fewer turns in agentic evaluations. This makes it one of the most cost-efficient models at its intelligence level, costing less than Qwen3.5 397B A17B (reasoning, $418) and Claude Sonnet 4.6 (non-reasoning, $1397). KAT-Coder-Pro V2 is currently priced at $0.30/$1.20 per 1M input/output tokens on StreamLake and AtlasCloud API endpoints.

➤ ⚡ Low end-to-end response time: KAT-Coder-Pro V2 runs at ~109 output tokens per second, far ahead of Claude Opus 4.6 (non-reasoning, 39 OTPS) and Claude Sonnet 4.6 (non-reasoning, 43 OTPS). Because it also has a low time to first token without any reasoning delay, it delivers one of the fastest end-to-end response times, which measures the time taken from request sent to final output returned.

Model details:

➤ Availability: KAT-Coder-Pro V2 is available via StreamLake and AtlasCloud API endpoints
➤ Context Window: 256K tokens (equivalent to KAT-Coder-Pro V1)
➤ Multi-modal capabilities: Text input and output only

[Dmitry [d9k] @d9k]

@diary_ru https://t.co/aMjrPowX7m Здесь пытаются воскрешать https://t.co/1b87BZTIPI на https://t.co/aooYrSw1Ob

[Prasenjit @prasenx]

full stack developer in 2025 be like

[Raja Koduri @RajaXg]

Reusable Chiplets across vendors (for AI)

[Dmitry [d9k] @d9k]

@shkotobaza Trump

[Dmitry [d9k] @d9k]

@shkotobaza 🎵Фотографирую закат
Будто пару лет назад
Без тебя, без тебя
Без тебя-я-я

[Интимный Дизайнер @vanessa1ask]

Шел 8 час
А я не могу остановиться
Надеюсь к понедельнику закончу 😂
А как вы проводите свои выходные ?

[Dmitry [d9k] @d9k]

#Nazi @kanyewest generated with #Grok_AI

[Dmitry [d9k] @d9k]

#Nazi @kanyewest generated with #Grok_AI

[Dmitry [d9k] @d9k]

@GingeronInc Рита, не грусти 😢

[Dmitry [d9k] @d9k]

@tatan_nene @Redshameless факт, объясняет логотип Starbucks

[еврейская кикимора @Redshameless]

какие ваши любимые не банальные теории заговора? ну типа не про массонов плоскую землю адренохром итд а чëто поинтереснее??

[Lily @AdrenaLily]

it works though

[тюня вафлин @tw0munn]

если существует социальный капитал, то где взять кредит?

[Dmitry [d9k] @d9k]

@tw0munn В этом плане игра "Кто хочет стать миллионером" реалистична, т. к. она про череду правильных выборов🤔. Можно запустить похожий проект с каверзными малоизвестными вопросами по бизнесу и маркетингу)

[Dmitry [d9k] @d9k]

@tw0munn главное, чтобы не джуна

[Dmitry [d9k] @d9k]

@tw0munn хм, может, стоит походить на записи подкастов)