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Latest news, beside the leaderboard

Read what just changed, and see who is ahead. Those are the two doors on this page.

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ClaudeDevsClaudeDevs·1h ago
🚀 Release

Claude Code Projects opens to every Pro and Max user on the waitlist: one conversation coordinating parallel cloud threads

On Oct 9 ClaudeDevs said every Pro and Max user on the Claude Code Projects waitlist has been let in. A project is a long-running coordinator conversation that spins each task into its own thread, usually a parallel cloud session on its own branch that opens a PR when needed; threads can also run locally via Remote Control. Still public beta; not yet on Team or Enterprise.

⚡ Key Takeaways
  • •From Oct 9, every Pro/Max user on the waitlist has access; still public beta, not on Team/Enterprise.
  • •A project is one coordinator conversation plus N threads, each with its own context window; cloud threads work on their own branch and open PRs.
  • •Since Sep 23, threads can run on your own machine via Remote Control when a task needs local tools.
  • •New threads inherit project instructions and memory, each repo's CLAUDE.md and skills, and your claude.ai connectors.
  • •Projects draw on the same plan limits as other Claude Code sessions and use them faster; no benchmarks were published.
Read details→
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Hugging Face Daily Papers@HuggingFace·1h ago
🔥 Trending

Opera: A Verbal Critic Framework for Long-Horizon Coding Agents Tracks Diagnosed Flaws Until Resolution to Boost SWE-Bench by 15%

Long-horizon coding agents tackling complex software repositories depend on timely guidance, yet conventional LLM critics often degrade agent outcomes by misinterpreting in-progress exploratory commands or offering ephemeral advice that is never tracked. Researchers from Rutgers and Lehigh University unveil Opera (arXiv:2609.33987), an open-source verbal critic framework that treats diagnostic corrections as persistent notes tracked until root problems are definitively resolved. Opera orchestrates reviews through hybrid periodic and event-driven triggers, verifies proposed critiques against visible terminal artifacts, and monitors downstream trajectories to distinguish mere superficial compliance from genuine resolution. As a test-time intervention, Opera elevates baseline agent resolve rates by 12.4 percentage points on Terminal-Bench 2.1, 15.0 on SWE-Bench Pro, and 8.9 on DeepSWE v1.1 across four foundation backbones. Furthermore, fine-tuning Qwen3.5-9B on Opera-guided rollouts yields a 10.2 percentage point gain on held-out repositories without any test-time critic, preserving stability across heterogeneous execution harnesses (such as OpenHands to Terminus-2).

⚡ Key Takeaways
  • •Rutgers and Lehigh release Opera, introducing persistent diagnostic notes that track diagnosed faults until proven resolution in coding agents
  • •Elevates resolve rates by 12.4 points on Terminal-Bench 2.1 and 15.0 points on SWE-Bench Pro across multiple policy models
  • •Fine-tuning Qwen3.5-9B on Opera rollouts yields a 10.2 point gain on held-out repos without test-time critics, preserving cross-harness stability
Read details→
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Hugging Face Daily Papers@HuggingFace·1h ago
🔥 Trending

Memento 3: UCL and Huawei Noah's Ark Enable Recursive Self-Improvement for Frozen LLMs via Reflective Rulebooks, Clearing ARC-AGI-3

Endowing artificial agents with general intelligence requires inferring environment dynamics and refining world models continuously in the wild. Fine-tuning models directly is prohibitively expensive and precipitates catastrophic forgetting. Researchers from University College London (UCL) and Huawei Noah's Ark Lab UK present Memento 3 (arXiv:2610.11794), a framework enabling frozen LLM agents to achieve model-based Recursive Self-Improvement (RSI) purely via external memory. The agent maintains a natural-language rulebook representing its evolving hypotheses of environment physics, which is compiled into executable code for fast simulation and action planning. Governed by a continuous observation-reflection-revision-compilation-verification loop, the system leverages prediction errors to refine rules. Edits are merged only after passing LLM semantic alignment audits and deterministic cell-exact replay verification. On the rigorous ARC-AGI-3 abstraction benchmark, Memento 3 solves 100% of levels across all 25 public environments, scoring a perfect 100.0 Relative Human Action Efficiency (RHAE) while utilizing only 44% of human action counts. In Atari Pong, a synthesized feedback controller shuts out opponents 21:0 across three evaluation seeds with zero test-time LLM inference.

⚡ Key Takeaways
  • •UCL and Huawei Noah's Ark introduce Memento 3, unlocking model-based Recursive Self-Improvement for frozen LLMs via executable rulebooks
  • •Compiles natural-language physics hypotheses into code world models validated through cell-exact replay verification
  • •Clears all 25 games on ARC-AGI-3 using only 44% of human actions, and delivers 21:0 Pong shutouts with zero runtime LLM calls
Read details→
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Hugging Face Daily Papers@HuggingFace·1h ago
🔥 Trending

Skill Constellations: The First Supply Chain Audit of 2.19M GitHub Agent Skills Reveals Vulnerability Propagation Patterns

Modern AI coding agents such as Claude Code, Codex, and terminal assistants routinely execute agent skills—instructions and executable scripts bundled in SKILL.md specifications—with full local user privileges. Developers share these skills primarily by copying files across repositories, inadvertently forging a shadow software supply chain without centralized registries, semver tagging, or provenance tracking. A seminal empirical audit by Fahd Seddik (arXiv:2610.11169) introduces Skill Constellations, constructing the first dated copy network of agent skills derived from git provenance across 2,193,119 skill adoptions on GitHub. The investigation demonstrates that a minuscule set of root repositories generates nearly all downstream copies, yet GitHub star counts correlate poorly with true lineage sources. Critically, downstream copies almost never adopt upstream security patches. By fitting a predictive copy network model, auditing just the top 100 identified root repositories halts 14.9% of subsequent high-risk skill adoptions (compared to a negligible 0.5% when inspecting the top 100 starred repos), proving the urgent necessity for decentralized package ecosystems to adopt versioned references over loose copies.

⚡ Key Takeaways
  • •Skill Constellations delivers the first dated supply chain network of 2.19M agent skill adoptions across GitHub repositories
  • •Reveals that a tiny cluster of progenitor repositories drives global adoption without correlating with GitHub star metrics
  • •Auditing the top 100 root repositories prevents 14.9% of subsequent high-risk skill adoptions, outperforming star-based audits by 30x
Read details→
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T4T5@t4t5·1h ago
🌟 Open Source

omdrop-owl: two-way AirDrop with iPhone on a Framework 13 Linux laptop via OWL, with Wi-Fi staying connected

On 2026-10-09 developer t4t5 open-sourced omdrop-owl, a radio backend for the Omarchy plugin omdrop that gives two-way AirDrop with an iPhone on the Framework 13's MediaTek MT7925 while Wi-Fi stays connected. It builds on Seemoo Lab's 2019 OWL/OpenDrop reverse engineering rather than a from-scratch effort. README self-tests: ~1.3 MB/s receive, ~490 kB/s send; the AP must be on channel 6/44/149.

omdrop-owl: two-way AirDrop with iPhone on a Framework 13 Linux laptop via OWL, with Wi-Fi staying connected
⚡ Key Takeaways
  • •Project: omdrop-owl, repo created 2026-10-08; 416 stars / 24 forks at ingest (GitHub API); no license declared
  • •Hardware: only MediaTek MT7925 (Framework 13) tested; two-way transfer with Wi-Fi staying connected
  • •Speed (author's README self-test): ~1.3 MB/s receive, ~490 kB/s send; start/stop about 2 s
  • •Limits: AP must be on channel 6/44/149; station may stop receiving 3–165 s after monitor teardown, so it reconnects
  • •Lineage: builds on Seemoo Lab's 2019 OWL/OpenDrop; omdrop PR #25 still open
Read details→
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DHH@dhh·4h ago
🚀 Release

Basecamp launches official hosted MCP server for ChatGPT, Claude, Cursor and Grok

37signals opened its hosted MCP endpoint at https://mcp.basecamp.com/mcp: OAuth sign-in, read-only or full access, free on every Basecamp account, covering projects, to-dos, card tables, docs, calendar and Campfire.

Basecamp launches official hosted MCP server for ChatGPT, Claude, Cursor and Grok
⚡ Key Takeaways
  • •Official hosted endpoint https://mcp.basecamp.com/mcp over HTTP, no setup on Basecamp's side
  • •Two access levels at approval: Read-only or Full access, scoped to exactly what the user can see
  • •Documented for ChatGPT (developer mode), Claude, Cursor and Grok, plus Claude Code and VS Code configs
  • •Free with every Basecamp account; the AI client may need a paid plan for custom connectors
  • •37signals says it does not train AI models on Basecamp content (basecamp.com/ai)
Read details→
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ChatGPTChatGPT·6h ago
🚀 Release

ChatGPT dots update: create your dot on iOS/Android and delegate work to Codex threads

OpenAI's Oct 9 dots update lets you create and customize a dot from the ChatGPT iOS and Android apps. Dots can now start work in Codex, follow up on existing threads using ChatGPT conversations, Codex threads and automations as context, and read and edit ChatGPT Work scheduled tasks.

ChatGPT dots update: create your dot on iOS/Android and delegate work to Codex threads
⚡ Key Takeaways
  • •Create, name, theme and connect plugins to a dot from the iOS/Android app
  • •Dots can start Codex work and continue existing threads, choosing when to start fresh
  • •Context from ChatGPT conversations, Codex threads and automations
  • •Dots can read and edit ChatGPT Work scheduled automations
  • •Announcement: ~1,090 likes, ~119K views
Read details→
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OpenAI DevelopersOpenAIDevs·7h ago
🚀 Release

Codex composer predictions enter beta: Codex suggests your next message, Tab to accept, free of usage for Pro

On Oct 9 OpenAI opened composer predictions in beta in the Codex desktop app for personal ChatGPT Pro users. After each response Codex may prefill your next message from the current thread; press Tab to accept and edit before sending. Local and SSH threads only, with GPT-6 Astra and GPT-6.1 Sol; generating predictions does not count toward usage limits during the beta.

Codex composer predictions enter beta: Codex suggests your next message, Tab to accept, free of usage for Pro
⚡ Key Takeaways
  • •Personal ChatGPT Pro (18+), Codex desktop app, local and SSH threads only
  • •Supported models: GPT-6 Astra and GPT-6.1 Sol
  • •Predictions are free during beta; sent messages bill normally
  • •Tab accepts without sending; disable via Settings → General → Composer → Show predictions
  • •Announcement post: ~3,250 likes and ~230K views within hours
Read details→
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Grok Botbot·8h ago
🚀 Release

Grok Bot gets its own email inbox: claim a @mail.grokbot.com address to sign up for services, contact businesses and schedule meetings

SpaceXAI's official @bot account announced on Oct 9 that Grok Bot is rolling out its own email inboxes. Ask your Bot to claim one and it gets a @mail.grokbot.com address it can use to sign up for services, contact businesses or schedule time; team admins must enable it.

Grok Bot gets its own email inbox: claim a @mail.grokbot.com address to sign up for services, contact businesses and schedule meetings
⚡ Key Takeaways
  • •Addresses live on @mail.grokbot.com; you can request a custom name and the Bot checks availability before claiming
  • •The official announcement post passed 3,300 likes; rollout started Oct 9 (PT)
  • •Team admins must enable inboxes for their team
  • •The official changelog (0.68.1) does not yet list the feature; send limits and retention are undisclosed
Read details→
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TestingCatalog Newstestingcatalog·9h ago
🚀 Release

Claude Managed Agents dynamic workflows hit public beta: the lead agent writes an orchestration program running up to 64 concurrent threads and 1,000 agents per run

Anthropic expanded dynamic workflows in Claude Managed Agents to public beta. With workflows enabled in an agent's multiagent block, Claude writes a workflow program that runs many agents in background phases and combines their results, aimed at audits, migrations, deep research and cross-checking.

⚡ Key Takeaways
  • •Enable with multiagent.type: "multiagent_20261001" and workflows: {"type":"enabled"} under the managed-agents-2026-04-01 beta header
  • •Up to 64 threads working at once per run and 1,000 agents over a run's life (thread_limit_error beyond)
  • •Runs last 24h by default; 10 open runs per session by default; runs don't nest
  • •No separate run price: thread tokens bill at model rates and count toward the session budget, which pauses runs when reached
Read details→
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Stanley WeiStanleyWei4748·9h ago
🚀 Release

Pine Computer launches a cloud computer built for AI agents: event-driven perception instead of screenshot polling; GPT-5.6 Luna hits 78.3% SaaS-Bench v1.1 checkpoint score vs 74.3% for Opus 5 + Claude Code at ~$1.02 model cost per task

On Oct 9 Pine AI released Pine Computer in private beta: cloud virtual computers plus a harness and runtime built for AI, driven by an API across browser, files and shell. Instead of repeated screenshots, the OS, browser and apps push change notifications to the model ("epoll for AI perception"). On SaaS-Bench v1.1 (106 tasks, 23 apps) GPT-5.6 Luna on Pine scored 78.3% on checkpoints vs 74.3% for Opus 5 + Claude Code, though its fully-resolved rate (27.4%) trails the latter (31.1%).

Pine Computer launches a cloud computer built for AI agents: event-driven perception instead of screenshot polling; GPT-5.6 Luna hits 78.3% SaaS-Bench v1.1 checkpoint score vs 74.3% for Opus 5 + Claude Code at ~$1.02 model cost per task
⚡ Key Takeaways
  • •SaaS-Bench v1.1 checkpoint score: Pine + GPT-5.6 Luna 78.3% vs Opus 5 + Claude Code 74.3% vs GPT-5.6 Sol + Codex 71.1%
  • •Fully resolved rate trails: 27.4% vs 31.1% (Claude Code) / 29.2% (Codex)
  • •Model token cost per task: ~$1.02 vs $26.50 (Opus 5 + Claude Code) / $20.50 (GPT-5.6 Sol + Codex), excluding infrastructure
  • •New computer boots in seconds, heavy state restores in ~15 s, paused ones resume in <1 s
  • •Launch post: ~99.8K impressions, 250+ likes, 120 reposts; private beta waitlist only
Read details→
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OpenAI DevelopersOpenAIDevs·10h ago
🚀 Release

Codex on Windows gets a Microsoft Execution Containers (MXC) sandbox: no admin setup, no extra accounts or firewall rules, native network policy and granular file access

On Oct 9 OpenAI Developers announced a new Codex sandbox mode on Windows built on Microsoft Execution Containers (MXC), promising faster setup, stronger network enforcement and granular file access controls on compatible Windows 11 devices. Docs now list MXC as the recommended implementation, with elevated/unelevated as legacy fallbacks. It ships in Codex CLI 0.162.0, where features.prefer_mxc is off by default in the standalone CLI; the desktop app enables it via rollout.

Codex on Windows gets a Microsoft Execution Containers (MXC) sandbox: no admin setup, no extra accounts or firewall rules, native network policy and granular file access
⚡ Key Takeaways
  • •Windows sandbox implementations go from 2 to 3: mxc (recommended) / elevated (preferred fallback) / unelevated (weaker network isolation)
  • •MXC needs zero admin elevation, zero extra Windows accounts, zero local firewall rules; commands run as the user with per-command policy
  • •Minimum Codex CLI 0.162.0; features.prefer_mxc is off by default in the standalone CLI
  • •Enterprises can block MXC with windows.allow_mxc = false in requirements.toml
  • •Official post: 650+ likes, 51.8K impressions within ~1.5 hours
Read details→
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ClaudeDevsClaudeDevs·15h ago
📉 Price Cut

Anthropic cuts Sonnet 5.5 cache reads to $0.10/MTok, adds $100–$200 monthly API credits to Max, ships Managed Agents automation playbook

Sonnet 5.5 cache hits now cost 0.05x base input ($0.10/MTok), which Anthropic says makes most agentic work ~20% cheaper. Max 5x/20x plans now include $100/$200 in monthly Claude API credits (Team $20–$100 per seat) usable on the API, Managed Agents and Agent SDK, alongside an official reference implementation for scheduled Managed Agents automations.

⚡ Key Takeaways
  • •Sonnet 5.5 cache reads $0.20 to $0.10/MTok (0.05x base input); input $2 / output $10 unchanged; Opus 5.5 also 0.05x ($0.20/MTok)
  • •Anthropic says ~20% cheaper on most agentic work; API only, Claude Code limits unchanged
  • •Max 5x gets $100/mo, Max 20x $200/mo; Team $20 (Standard) / $100 (Premium) per seat, pooled up to $500; no rollover
  • •Credits cover Claude API, Managed Agents, Agent SDK and playground, not Claude Code or app extra usage
  • •Managed Agents bills tokens plus $0.08 per session-hour; official daily-brief template sets up via a Claude Code command
Read details→
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Anvishaanvisha·17h ago
🚀 Release

Voyager launches: a desktop agent harness that drives Blender, DaVinci Resolve, After Effects and Ableton — 'the Codex for creative work'

Nullframe (the Moda team, YC F26) shipped Voyager, a local desktop agent harness that drives creative apps through their own scripting APIs, ships free Design/Video/DAW engines, and works with your own Claude/Codex sign-in or API keys. The launch post passed 1.48M impressions.

Voyager launches: a desktop agent harness that drives Blender, DaVinci Resolve, After Effects and Ableton — 'the Codex for creative work'
⚡ Key Takeaways
  • •Launch post: ~1.48M impressions, 3,074 bookmarks, 2,457 likes on X
  • •Drives Photoshop, Illustrator, After Effects, Premiere Pro, DaVinci Resolve, Final Cut Pro, Blender, Unity and Ableton Live; skills also cover Cinema 4D, Houdini, Remotion, Manim
  • •~40 built-in skills, MCP server support, and reuse of skills installed for Claude Code / Codex / Cursor
  • •Free app with BYO agent/keys; paid plans from $19/mo, generation billed at provider cost with no markup
  • •Apple Silicon + macOS 15 required; Windows 11 / Linux in alpha; desktop v0.1.84 shipped Oct 8
Read details→
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Odyssey@odysseyml·19h ago
🚀 Release

Odyssey launches Odyssey-3 world model: new SOTA 66.1 on Physics-IQ Verified, free real-time browser preview, and robot-arm control

On Oct 8 Odyssey released Odyssey-3, a foundation world model built as an autoregressive diffusion transformer. Odyssey-3 Pro (720p) scores 66.1 on Physics-IQ Verified video-to-video, the highest reported score, and 54.7 image-to-video. A free browser research preview (Flash variant) offers first/third-person navigation and free camera; API access is by request, with no open weights or public pricing. Odyssey says tens of hours of demos are enough to control various robot arms.

Odyssey launches Odyssey-3 world model: new SOTA 66.1 on Physics-IQ Verified, free real-time browser preview, and robot-arm control
⚡ Key Takeaways
  • •Physics-IQ Verified v2v: Odyssey-3 Pro 66.1 (best-of-8, highest reported) / 63.4 prompt-enhanced; 480p model 51.8 → 61.6 → 64.4 (launch post)
  • •Image-to-video: Odyssey-3 Pro 54.7; vendor says 1st in 3 of 4 WorldMark categories (self-reported)
  • •Architecture: autoregressive diffusion transformer predicting environment evolution in real time from past observations plus latest actions/events
  • •Physical AI: an action decoder trained on tens of hours of demos controls robot arms, with recovery behaviors absent from training data (technical write-up)
  • •Access: free browser research preview; API by request, no open weights or public pricing
Read details→
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IQuest Research@IQuestLab·22h ago
🔥 Trending

IQuest-Q1 open-weights 320B MoE coding agent: 15B active / 524K context; DeepSWE 64.6, Terminal-Bench 2.1 83.2

IQuest Research’s IQuest-Q1 (~320B total / 15B active, 524K context) targets repo-level coding, terminal work, and long-horizon tool use. Weights and serving images are on Hugging Face / GitHub. Self-reported same-pipeline scores: DeepSWE v1.1 64.6, NL2Repo 63.0, CyberGym 84.5, Terminal-Bench 2.1 83.2. Ships with SGLang/vLLM images and Claude Code / Codex integration notes.

IQuest-Q1 open-weights 320B MoE coding agent: 15B active / 524K context; DeepSWE 64.6, Terminal-Bench 2.1 83.2
⚡ Key Takeaways
  • •Spec: ~320B MoE / ~15B active, 88 layers, 256 experts / 8 active, 524,288 context; hybrid 3×SWA+1×FA (HF card)
  • •Agentic coding (self-reported): DeepSWE v1.1 64.6 (DeepSeek-V4.1-Flash 74.2 / Opus 5 73.7); NL2Repo 63.0 (Opus 5 75.3)
  • •Terminal / cyber: Terminal-Bench 2.1 83.2; CyberGym 84.5 (tied with GLM-5.3; Flash 88.1)
  • •Post-train: SFT+RL plus Multi-Teacher On-Policy Distillation (MOPD); vendor flags early-stage, text-only limits
  • •Ship: hf download IQuestLab/IQuest-Q1 + sglang-iquest-q1 / vllm-iquest-q1 images (tp=8); Claude Code 2.1.140 / Codex 0.142 notes
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Cline@cline·22h ago
🚀 Release

Cline launches Cloud Agents: assign tasks in the browser, cloud sandboxes code/test and open PRs, up to 10 in parallel

Cline moved its open coding agent into the browser: connect GitHub, pick a repo and model, and each task runs in an isolated cloud sandbox that commits to a `cline/` branch and can open a PR—even with your laptop closed. Limits: 10 concurrent sessions and 50 new sessions/day. Providers: ClineFree, ClinePass ($9.99), and usage-billing. Cloud sessions do not yet load Rules, Skills, MCP, or Connectors.

⚡ Key Takeaways
  • •Surface: no install; assign work from app.cline.bot Agents; each session gets its own sandbox and repo copy (docs)
  • •Delivery: continuous commits on a dedicated cline/ branch, then optional PR; idle 15 minutes pauses the sandbox, resume keeps the workspace
  • •Scale: up to 10 concurrent sessions and 50 new sessions/day; mobile browser for approvals/follow-ups
  • •Models: ClineFree trials, ClinePass $9.99/mo (~2–5× open-model usage), usage-billing; switch mid-session
  • •Security / gaps: GitHub token scoped to the single chosen repo; cloud does not load Rules/Skills/MCP/Connectors yet (local IDE/CLI/Desktop remain full-featured)
Read details→
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JetBrains@JetBrains·1d ago
🔥 Trending

JetBrains ships Mellum2.1: 12B MoE (2.5B active) open coding-agent model, SWE-bench Verified jumps 2.0→47.0

On Oct 8 JetBrains released Mellum2.1 Thinking: same 12B MoE / 2.5B active / 131K / Apache 2.0 architecture, with gains almost entirely from large-scale RL in real sandboxes. Self-reported same-pipeline scores: SWE-bench Verified 47.0 (vs Mellum2 2.0), LiveCodeBench v6 82.0. On Hugging Face; vLLM serve now; GGUF/MTP coming soon.

⚡ Key Takeaways
  • •Spec: 12B MoE / 2.5B active, 131K context, Apache 2.0; architecture unchanged vs Mellum2 (HF card)
  • •Agentic jump (same pipeline): SWE-bench Verified 2.0→47.0, SWE-bench Pro 0.0→28.0, Terminal-Bench 2.1 0.6→17.4 (Pi v0.73.1)
  • •Coding: LiveCodeBench v6 82.0 (leads Qwen3.5-9B 75.4), HumanEval+ 91.5, BFCL v4 62.3
  • •Speed: fastest under load in JetBrains’ group; MTP ~1.6× single-request; still trails Qwen3.5-9B on SWE Verified 50.0 / Pro 38.0
  • •Ship: vllm serve JetBrains/Mellum2.1-12B-A2.5B-Thinking --reasoning-parser qwen3; GGUF/Ollama/LM Studio/MTP head coming (blog)
Read details→
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Anthropic@AnthropicAI·1d ago
🚀 Release

Anthropic launches Cyber Mission: free OSS Scanner with frontier models, plus Critical Infrastructure Defense with 11 partners

On Oct 8 Anthropic launched the Cyber Mission: (1) free opt-in OSS Scanner for critical open-source projects using strongest models including Claude Mythos, with PoC/explanation/candidate patches and >90% expected true-positive rate, no human triage; (2) Critical Infrastructure Defense Program with 11 founding partners including CrowdStrike, Palo Alto, Dragos, and Rockwell. Project Glasswing has surfaced 29,000+ candidate vulns.

⚡ Key Takeaways
  • •Two tracks: free opt-in OSS Scanner (model-only reports) + Critical Infrastructure Defense Program (OT/power/water/transport; 11 founding partners)
  • •Glasswing legacy: 29,000+ candidate vulns, ~6,000 human-triaged; ~5,000 reports sent when maintainers asked for bulk
  • •Quality bar: 88% of 97 critical/high samples met CVD bar; expected true-positive >90% (no human review; severity can be off)
  • •Enroll: core maintainers PR into Anthropic’s enrollment repo; also Claude for OSS free Max + Cyber Verification Program
  • •Framing: OSS-Fuzz analogue for LLM scanning; enterprise Claude Security remains separate (research post)
Read details→
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Grok Imagine@imagine·1d ago
🔥 Trending

Grok Imagine Video 1.5 Lite hits the API: workhorse text/image-to-video from $0.02/s at 480p, about a quarter of Video 1.5's list price

On 2026-10-08 xAI shipped grok-imagine-video-1.5-lite in the Grok Imagine API: text/image-to-video with native lip-synced audio, 1–15 s, at $0.02/s (480p), $0.03/s (720p), and $0.14/s (1080p, upscaled from 720p). No reference images, voices, or keyframes; those stay on Video 1.5 ($0.08/s). Batch API supported; no quality evals published.

Grok Imagine Video 1.5 Lite hits the API: workhorse text/image-to-video from $0.02/s at 480p, about a quarter of Video 1.5's list price
⚡ Key Takeaways
  • •Pricing: $0.02/s 480p, $0.03/s 720p, $0.14/s 1080p
  • •List price: Lite $0.020/s vs Video 1.5 $0.080/s, about 1/4
  • •Specs: text/image-to-video, 1–15 s, native lip-synced audio; 1080p upscaled from 720p
  • •Not supported: reference images (1.5: up to 14), voice refs, first/last frames, keyframes
  • •Access: Batch API, 10 RPS, us-east-1/us-west-2; no quality benchmarks published
Read details→