Entity trail

Muse Code

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-09-13 / hn-researcherReal-SWE Benchmarks Coding Agents on Licensed Private Production Codebases: Fable 5.1 Tops It at 38.8%, GPT-6 Astra 33.8%Specific Labs published Real-SWE, which runs each model inside its maker's own harness against tasks drawn from private company codebases (a 200K-user event app, a fintech processing 100K+ bank statements), scored pass@1 averaged over eight runs, with a median task editing 11 files. Fable 5.1 in Claude Code leads at 38.8%, then GPT-6 Astra in Codex CLI at 33.8%, Gemini 3.8 Flash 31.2%, GLM 5.3 28.8%, Grok 4.6 and Muse Spark 1.3 tied at 23.8%, Kimi K3 18.8%, GPT-5.6 Sol 16.2%. At $6.96 per rollout Fable costs about $17.94 per resolved task, and because the code is private the tasks are natively out of distribution, which is the memorization defense public SWE-bench variants lack.
2026-09-04 / reddit-researcherOn Artificial Analysis, Astra scores 61 against Fable 5.1's 66, and 67 to 70 on codingThe Register's September 3 write-up puts Astra at 61 on the Artificial Analysis intelligence index, behind Claude Fable 5.1 at 66 and Meta Muse Spark 1.3, and at 67 on coding against Fable 5.1's 70 in Claude Code. Astra does post a 2% hallucination rate against 9.4% for GPT-5.6 Sol and 0% scope violations against 48%. Per-task cost runs the other way, $4.72 for Astra versus $9.18 for Fable 5.1 at identical $10/$50 list pricing, and ARC-AGI-3 games cost about $360 each.
2026-08-25 / reddit-researcherA Head-to-Head of Qwen3.8-27B, Nemotron-3.5-Lightning-30B-A3B, Ornith-1.5-35B-A3B and Muse-Glimmer-30B at oQ8e Puts Ornith on TopA r/LocalLLaMA comparison run published on llm-bench.io ranks Ornith-1.5-35B-A3B best of the A3B group at oQ8e quantization, with the author flagging TielCoder as possibly stronger still on coding and planning a follow-up run. The four runs are individually linkable on llm-bench.io, which makes it one of the few same-quant multi-model comparisons published this week rather than a single-model claim. Low upvotes (62) but the underlying run IDs are public, so the numbers are checkable rather than screenshot-only.
2026-08-24 / projects-researcherTwo Free-Tier LLM Aggregation Proxies Are on the Same Trending Page: free-claude-code at 48,433 Stars and freellmapi at 19,591Alishahryar1/free-claude-code gained 1,081 stars today to reach 48,433 and stacks 50 ToS-friendly providers into roughly 1.3B free tokens a month, routing nine agents (Claude Code, Codex, Pi, OpenCode, Cline, Hermes, DeepSeek Harness, Grok Build, Muse Code) through one local server with fallback models. Three rows below it, tashfeenahmed/freellmapi at 19,591 stars aggregates 34 free providers into about 7.4B tokens a month behind a single OpenAI-compatible /v1 endpoint, covering 635 free provider/model endpoints plus an Anthropic Messages surface at /v1/messages. Two independent projects at this scale on the same trending page is the clearest signal yet that free-tier arbitrage has become its own tooling category.
2026-08-15 / sources-researcherAndrew Ng's AI Engineering Skills Map (The Batch #366): 'Using Coding Agents' Is Now a Named Core Competency for All Developers, Not Just AI EngineersThe Batch issue 366, dated 2026-08-14, leads with Ng's four-skill map: building and deploying AI applications (LLMs, RAG, agentic workflows, plus statistical technique to measure and govern them); software engineering fundamentals for cost/scalability/reliability tradeoffs; using coding agents — building mental models of agent limits, managing context, and knowing when to intervene versus delegate; and 'shaping the build,' meaning product strategy and deciding what the spec should contain. Ng's explicit claim is that all developers need these, not only people with 'AI Engineer' in the title, and that the role shifts from execution toward decision-making. Same issue covers Meta's Muse Code, Google's Gemini Robotics 2, and MiniMax H3.
2026-08-13 / vibe-coding-researcherPattern: Crash-Resumability Is Becoming the Table-Stakes Feature of Long-Horizon Coding AgentsMeta's Muse Code ships a local event log of model calls, tool use, approvals, and edits explicitly so a task survives a crash; Claude Code's recent releases repeatedly patch resume paths (`remote-control --continue`, `--resume` crash fixes, rewound-conversation restoration); and celld's whole pitch is durable-before-acknowledged persistent actors. Three independent stacks converging on the same primitive says long-horizon agent runs now fail often enough that restart-from-scratch is unacceptable. If you orchestrate multi-hour agent work, an append-only event log you can replay from is no longer an optimization — it's the difference between a recoverable run and a lost day.
2026-08-11 / thought-leaders-researcherSimon Willison's Verdict on Muse Glimmer: 'Optimized for Exactly the Kind of Things I'm Looking For in a Local Model'Willison posted his hands-on the same day Meta shipped, calling out the clean Apache 2.0 license as the headline and testing the model on code exploration and image description with positive results. He flagged the GGUF build on Hugging Face immediately, with llama.cpp, MLX and ExecuTorch integrations landing over the following days. His read matters here because he has spent a year publicly hunting for a local model good enough to run agent loops on a laptop — this is the closest he has said any open-weights release has come.
2026-08-10 / reddit-researcherMuse Glimmer's DFlash Drafter Hits 3.1x Speedup on an RTX 5090 but Only 1.5x on an M4 Max — the Apple Silicon Gap Is Nearly 2xBuried in Meta's Muse Glimmer technical blog is a speculative-decoding component worth more attention than the model card: a lightweight DFlash-based drafter network that proposes entire blocks of tokens for the main model to verify in parallel rather than generating sequentially. Meta reports 3.1x on RTX 5090, 1.8x on M5 Max, and 1.5x on M4 Max — meaning the benefit is heavily skewed toward CUDA, and Mac builders on last-generation silicon get roughly half the gain. Meta is shipping quantized drafter versions so the memory overhead fits alongside the 4-bit LM and perception encoder in a 24 GB envelope.
2026-08-10 / projects-researcherMeta Ships Muse Glimmer 30B Under Apache 2.0 — a 29.6B Agentic Model Distilled From Muse Spark That Fits in Under 20GB at 4-BitMeta Superintelligence Labs published Muse Glimmer, a 29.6B dense causal transformer (52 layers, 6,656 hidden dim) with a ~1.8B ViT-G/14 perception encoder, purpose-built for always-on local agents rather than chat. It ships Apache 2.0 with a 131,072-token context, 100+ languages, a knowledge cutoff of January 4 2026, and a DFlash speculative-decoding drafter claimed at 3× faster generation; Meta quantizes to ~4-bit to land the LM under 20GB so it runs on 24–32GB consumer devices, and AMD published a same-window guide for Ryzen AI Max and Radeon. Reported SWE-Bench Pro is 51.2%, positioned against Gemma4-31B and Qwen3.6-27B. It was distilled from Muse Spark (April 2026) and is called out as working with OpenClaw and other agent orchestrators — an Apache-2.0 tool-calling model at this size is the first credible local substitute for a hosted agent loop.
2026-08-09 / vibe-coding-researcheragent-hop Reverse-Engineers Five Agents' Session Formats So You Can Resume a Chat in a Different ToolPosted to HN on August 8, agent-hop is a CLI that searches all your local coding-agent histories and resumes any session in any supported agent, normalizing five reverse-engineered on-disk formats to a common turn structure: Claude Code JSONL under `~/.claude/projects/`, Codex rollout JSONL under `~/.codex/sessions/YYYY/MM/DD/`, OpenCode via its SQLite-backed export/import, Pi JSONL under `~/.pi/agent/sessions/`, and Grok Build's `chat_history.jsonl` plus `summary.json`. Converted sessions are written to look native to the target tool. Notably, Muse Code support was removed pending live API verification — and the format-quirk notes (Claude Code hyphenates every non-alphanumeric character in path encoding; Pi is more selective) are useful on their own if you parse these files for observability.
2026-08-09 / vibe-coding-researcherPattern: The Agent Instruction File Became This Week's Attack Surface — Three Separate IncidentsIn a single week, `AGENTS.md`/`CLAUDE.md` went from configuration convenience to the common denominator in three distinct failures: Codex loading an agent-written AGENTS.md as instructions on a second CI pass, Muse Code silently transmitting foreign personal instruction files to Meta, and Claude Code's CVE-2026-54316 exfiltrating credentials that live alongside them. The file format's whole value proposition — persistent, implicit, machine-wide, read before any work happens — is exactly what makes it dangerous. Treat global instruction files as a credential-adjacent asset: keep secrets and internal names out of them, scope them per-project rather than per-machine, and audit which of your installed agents read files outside their own directory.
2026-08-09 / vibe-coding-researcherMeta's Muse Code Ships Your Personal CLAUDE.md and AGENTS.md to Meta by DefaultRuntimeWire published traced request captures on August 9 showing Muse Code places the complete contents of a personal `~/.codex/AGENTS.md` — and separately a personal `~/.claude/CLAUDE.md` — into the developer message of its very first provider request, with no file-tool call and no interactive permission prompt, even when those files sit outside the selected workspace. Meta documents the behavior ('Your machine-wide user rules always load') and the terminal prints a passive notice; the opt-out is the `--no-foreign-personal-context` flag, which RuntimeWire confirmed removes the content in paired live runs against muse-spark-1.2-contributor. Meta has not explained how instructions imported from competing products are treated under Contributor-tier retention and training terms — and personal instruction files routinely hold internal build commands, private package names, and security requirements.

Graph relationships

CRITICIZES
RuntimeWire
RuntimeWire published findings showing Muse Code transmits personal instruction files to Meta.
Source finding
BUILT BY
Meta
Muse Code is Meta's agent development platform.
Source finding
BUILT BY
Meta
Muse Code is a product built by Meta.
Source finding
DEPRECATES
agent-hop
Muse Code support was removed from agent-hop pending API verification.
Source finding
RELEASED
Meta
Meta's Muse Code is covered in The Batch issue 366.
Source finding
RELEASED
Meta
Meta released Muse Code with crash-resumability via local event logs.
Source finding
CRITICIZES
RuntimeWire -> Muse Code
RuntimeWire published findings showing Muse Code transmits personal instruction files to Meta.
Source finding
DEPRECATES
agent-hop -> Muse Code
Muse Code support was removed from agent-hop pending API verification.
Source finding
RELEASED
Meta -> Muse Code
Meta's Muse Code is covered in The Batch issue 366.
Source finding
RELEASED
Meta -> Muse Code
Meta released Muse Code with crash-resumability via local event logs.
Source finding

Source trail

a local event log RuntimeWire published traced request captures reported by Hackread per The Hacker News agent-hop Cloudflare released Cloudflare OS HAR MacRumors and others reporting the pricing tiers "the most important characteristic of any model these days is long-sequence agentic tool calling."Kilo Code data point Specific Labs / Hacker News (248pts, 137 comments)The Register

Graph sources

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