inertia

[inertia @entropymerchant]

🤌

[Z.ai @Zai_org]

GLM-5.2 leads GLM-5.1 by a wide margin across various domains, including coding, tool usage, reasoning, and general knowledge.

[inertia @entropymerchant]

@_xjdr 🔥

[inertia @entropymerchant]

🔥

[Kimi.ai @Kimi_Moonshot]

🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced!

🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite.
🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6.
🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates.

⚡️ 6x High-Speed Mode coming soon!
🔌 Available today via Kimi API and Kimi Code.

🔗 Kimi Code: https://t.co/uvoSJKyGCY
🔗 API: https://t.co/EOZkbOwCN4

[inertia @entropymerchant]

cancelled no fills

[inertia @entropymerchant]

$AAPL sell programs activate at 317

[inertia @entropymerchant]

@beffjezos

[inertia @entropymerchant]

😎

[MiniMax (official) @MiniMax_AI]

Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities

- Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency, 28.8% KernelBench Hard, 74.2% MCP Atlas
- MiniMax Sparse Attention scales context to 1M
- Natively Multimodal from Step Zero

API: https://t.co/fHRdSV7BwZ
Token Plan: https://t.co/BDCycxepZw
🚀New! MiniMax Code: https://t.co/GvB4YiB6Ul

Weights & Tech Report in ~10 Days

[inertia @entropymerchant]

$TLT buy programs activate at 83.33

[inertia @entropymerchant]

Leaning in here at 532 with average fill price of 511 in the short

[inertia @entropymerchant]

$SOXX sell programs activate here at 490

[inertia @entropymerchant]

V4 flash
$0.14 in
$0.28 out
1M context
incredible performance/$

[inertia @entropymerchant]

🤩

[DeepSeek @deepseek_ai]

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length.

🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models.
🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice.

Try it now at https://t.co/GCdiMzk1Dl via Expert Mode / Instant Mode. API is updated & available today!

📄 Tech Report: https://t.co/drlDrxkYtp
🤗 Open Weights: https://t.co/T13Y8i7SDM

1/n

[inertia @entropymerchant]

Covered here 385

[inertia @entropymerchant]

$CAR sell programs activate here at 615

[inertia @entropymerchant]

@zan2434 @eddiejiao_obj @drewocarr High taste

[inertia @entropymerchant]

@demishassabis @AcerFur @Steve_Yegge 👀

[inertia @entropymerchant]

Sold here 385

[inertia @entropymerchant]

$MSFT buy programs activate at 367

[inertia @entropymerchant]

mamba3
paper https://t.co/651lAONGfB

code https://t.co/sWiZNO7d26

blog https://t.co/R9YgX1Oikh

[Albert Gu @_albertgu]

Paper: https://t.co/FHAWM26E1c
Code: https://t.co/IwEhuUSZVJ
Blog: https://t.co/GgcQUctmfZ
https://t.co/3jW3BCUZni

As usual, Mamba models can be applied to any modality. We focused on language modeling, where it dominates its predecessor Mamba-2 as well as other commonly used linear models.

[inertia @entropymerchant]

nvda moe
https://t.co/mDOS5gtAjE

https://t.co/EuyfQBKYrd