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TypeSafe AI just launched Jev: a dedicated System 1 decision model delivering 70ms responses, 4¢/1M input tokens, and free outputs. Here is how it compares to frontier LLMs:
TypeSafe AI just launched Jev: a dedicated System 1 decision model delivering 70ms responses, 4¢/1M input tokens, and free outputs. Here is how it compares to frontier LLMs:
130 native e-commerce & marketing endpoints controlled via conversational AI agents. Here is how it works:
130 native e-commerce & marketing endpoints controlled via conversational AI agents. Here is how it works:
Individual private storage, zero shared chat history, and Gemini 3 Pro reasoning. Here is how family pooling works:
Individual private storage, zero shared chat history, and Gemini 3 Pro reasoning. Here is how family pooling works:
• 6 total people share 1 subscription
• 5 TB shared storage pool
• Gemini 3 Pro + Workspace AI for all
• Antigravity quotas refreshed
• Jio 5G 18-month free offer explained
Full tutorial in reply 👇
• 6 total people share 1 subscription
• 5 TB shared storage pool
• Gemini 3 Pro + Workspace AI for all
• Antigravity quotas refreshed
• Jio 5G 18-month free offer explained
Full tutorial in reply 👇
• GPT-6 Sol: 50% price reduction ($2/$10 per 1M tokens)
• 90% prompt caching cut down to $0.20/M
• 1.05M context window (922K in / 128K out)
• 33.2% AutomationBench autonomous coding
• GPT-6 Luna: $0.10/M utility tier at 175 tok/s
Full archi…
• GPT-6 Sol: 50% price reduction ($2/$10 per 1M tokens)
• 90% prompt caching cut down to $0.20/M
• 1.05M context window (922K in / 128K out)
• 33.2% AutomationBench autonomous coding
• GPT-6 Luna: $0.10/M utility tier at 175 tok/s
Full archi…
• 66.4% Terminal-Bench record (#1 in coding)
• Fable 5.1 power at 40% lower cost ($4/$20)
• 1,846 Elo on GDPval-AA (+304 over GPT-6 Astra)
• $0.20/M cache reads (-60% price drop)
• +20% 5-hour limit boost in Claude Code
Full architectural review in reply 👇
• 66.4% Terminal-Bench record (#1 in coding)
• Fable 5.1 power at 40% lower cost ($4/$20)
• 1,846 Elo on GDPval-AA (+304 over GPT-6 Astra)
• $0.20/M cache reads (-60% price drop)
• +20% 5-hour limit boost in Claude Code
Full architectural review in reply 👇
• 2.1T MoE parameter scale
• 500k context window
• The RL quitting flaw explained
• 64.0% EEBench (#1 over Claude Fable & GPT-5.6)
• 71.0% DeepSWE
• $2/$6 per 1M tokens
Full guide in reply 👇
• 2.1T MoE parameter scale
• 500k context window
• The RL quitting flaw explained
• 64.0% EEBench (#1 over Claude Fable & GPT-5.6)
• 71.0% DeepSWE
• $2/$6 per 1M tokens
Full guide in reply 👇
• Summon instantly anywhere via Alt + Space
• 1-click active screen capture & multimodal analysis
• Drag-and-drop local files & code
• Powered by Gemini 2.5 with 2M context
Full technical breakdown in reply 👇
• Summon instantly anywhere via Alt + Space
• 1-click active screen capture & multimodal analysis
• Drag-and-drop local files & code
• Powered by Gemini 2.5 with 2M context
Full technical breakdown in reply 👇
👇 Full architectural breakdown and review in the first reply!
👇 Full architectural breakdown and review in the first reply!
Review: https://softreviewed.com/meta-muse-ai-agent-review/
Watch: https://youtu.be/Uq5UbLf1a4w
Review: https://softreviewed.com/meta-muse-ai-agent-review/
Watch: https://youtu.be/Uq5UbLf1a4w
• Surgical comment edits with zero face warping
• 50% lower generation latency
• Two new developer models (Flare & Sunburst)
• Native transparent PNG cutouts
Full technical guide in reply 👇
• Surgical comment edits with zero face warping
• 50% lower generation latency
• Two new developer models (Flare & Sunburst)
• Native transparent PNG cutouts
Full technical guide in reply 👇
• Eligibility check & activation
• Desktop app Astra setup
• Safe cancellation walkthrough
Full tutorial in reply 👇
• Eligibility check & activation
• Desktop app Astra setup
• Safe cancellation walkthrough
Full tutorial in reply 👇
• Ads matched to real-time conversational context
• High intent solution-seeking placements
• New attribution & landing page dynamics
Full guide in reply 👇
• Ads matched to real-time conversational context
• High intent solution-seeking placements
• New attribution & landing page dynamics
Full guide in reply 👇
• System-wide speech to text (Word, Notion, browser)
• Hold-to-talk & hands-free toggle modes
• Custom dictionary fixes jargon typos
Full guide in reply 👇
• System-wide speech to text (Word, Notion, browser)
• Hold-to-talk & hands-free toggle modes
• Custom dictionary fixes jargon typos
Full guide in reply 👇
• 95.9% BenchCAD (#1 3D vision-to-CAD synthesis)
• 64.6% Terminal-Bench Science
• 99.9% ARC-AGI-3 visual inductive logic
• Autonomous computer-use in Blender, Excel & KiCad
• 100% of…
• 95.9% BenchCAD (#1 3D vision-to-CAD synthesis)
• 64.6% Terminal-Bench Science
• 99.9% ARC-AGI-3 visual inductive logic
• Autonomous computer-use in Blender, Excel & KiCad
• 100% of…
• 75.4% DeepSWE v1.1 (#1 worldwide pass rate)
• 88.8% Terminal-Bench 2.1
• 59.4% SWEAtlas monorepo comprehension
• 1M Context Horizon (98.1% needle retention)
• Flat $5/mo developer plans & $0.10/1M API tok…
• 75.4% DeepSWE v1.1 (#1 worldwide pass rate)
• 88.8% Terminal-Bench 2.1
• 59.4% SWEAtlas monorepo comprehension
• 1M Context Horizon (98.1% needle retention)
• Flat $5/mo developer plans & $0.10/1M API tok…
• 75.4% DeepSWE v1.1 (#1 worldwide pass rate)
• 88.8% Terminal-Bench 2.1
• 59.4% SWEAtlas monorepo comprehension
• 1M Context Horizon (98.1% needle retention)
• Flat $5/mo developer plans & $0.10/1M API tok…
• 75.4% DeepSWE v1.1 (#1 worldwide pass rate)
• 88.8% Terminal-Bench 2.1
• 59.4% SWEAtlas monorepo comprehension
• 1M Context Horizon (98.1% needle retention)
• Flat $5/mo developer plans & $0.10/1M API tok…
89.4% on Terminal-bench 2.1 (#1 in the world). 85% cost collapse.
Full benchmark review in the reply below! 👇
89.4% on Terminal-bench 2.1 (#1 in the world). 85% cost collapse.
Full benchmark review in the reply below! 👇
• 52.6% Terminal-Bench-Science (2x Fable 5)
• 55.8% Terminal-Bench 4.0 Coding
• 75% cheaper cache reads ($0.25/M tokens)
• 1M context window + 128K max output
Full breakdown in reply 👇
• 52.6% Terminal-Bench-Science (2x Fable 5)
• 55.8% Terminal-Bench 4.0 Coding
• 75% cheaper cache reads ($0.25/M tokens)
• 1M context window + 128K max output
Full breakdown in reply 👇
👇 Full YouTube tutorial linked in the reply below:
👇 Full YouTube tutorial linked in the reply below:
👇 Watch the full YouTube guide below!
👇 Watch the full YouTube guide below!