Entries matching “intel”

@mgaruccio

@mgaruccio

A vLLM-XPU and DFlash recipe for Muse Glimmer 30B on a single Intel Arc Pro B70, reporting 278 aggregate tok/s across eight clients and an 840.8 tok/s burst peak at concurrency 96.

Artificial Analysis

@ArtificialAnlys

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta to be released under Apache 2.0 Muse Glimmer (high) arrives 16 months after

Artificial Analysis

@ArtificialAnlys

Meta's Muse Spark 1.1 scores 51 on the Artificial Analysis Intelligence Index and is cost and token efficient compared to its peers Muse Spark 1.1 (xhigh) improves 8 points over Muse Spark 1.0 (43) in three months. It is effectively tied with GLM-5.2 (max), GPT-5.4 (xhigh), and

@LilMuh

@LilMuh

Since Muse for Mac ships only for Apple silicon, this small service lets Muse's cloud VM screenshot, click and type on an Intel Mac, compressing each 5K frame to about 150 KB and handling Retina coordinate scaling.

Muse Glimmer 30B quantized with Intel AutoRound at a 3.5-bit target and packed with llm-compressor, tested on vLLM.

Artificial Analysis

@ArtificialAnlys

Meta is back! Muse Spark scores 52 on the Artificial Analysis Intelligence Index, behind only Gemini 3.1 Pro, GPT-5.4, and Claude Opus 4.6. Muse Spark is the first new release since Llama 4 in April 2025 and also Meta's first release that is not open weights Muse Spark is a new

@newjordan

@newjordan

A tested Muse Glimmer 30B Q4_K_M serving package for Intel Arc Pro B70 with full 131k context, reporting 19.0 tok/s decode at 129k cached and 503 tok/s full-context prefill.

@BrokkAi

@BrokkAi

muse-acp is a dependency-free Rust bridge between the Agent Client Protocol and Muse Code's Muse Session Protocol, letting developers use their Muse Code subscription inside Zed, IntelliJ IDEA and other JetBrains IDEs.

eesel AI reports Muse Spark 1.3 ranks #6 on the Artificial Analysis Intelligence Index, leads long-context and coding rows, but trails Claude Opus 5 on four of six agent evals.

Meta's launch post for Muse Glimmer, an Apache 2.0 30B model for local agents that fits in ~20GB at 4-bit and runs on M4/M5 Max Macs, RTX 5090s or 24–32GB GPUs.

Super-Intelligent-Investor( Investing in SI)

@iamchshah

Just enjoyed a coffee in Amsterdam while my AI assistant @Muse found the best canal cruise nearby, booked it, and paid for it. I never left my chair or browsed the web. This is the future. $META @alexandr_wang

+1

Artificial Analysis

@ArtificialAnlys

Meta has released Muse Spark 1.2. It's their third release in four months and scores 54 on the Artificial Analysis Intelligence Index, significantly improving agentic knowledge work capabilities over prior releases and putting Meta next to SpaceXAI in a tie for third place

I made a 400 page pdf html docs words txt from 400 Google docs any ai/agent app can't make it I Tried

@mjsabby

@mjsabby

An OpenAI- and Anthropic-compatible serving stack for Muse Glimmer 30B on one or two Intel Arc Pro B70s, built oracle-first with a float64 CPU reference that gates every GPU kernel.

Artificial Analysis

@ArtificialAnlys

At 30B parameters, Muse Glimmer sits near the Intelligence vs Parameters frontier for open weights models: 5 points above Gemma 4 31B (Reasoning) at the same size, effectively matching Kimi K2.5 (Reasoning) at 33x fewer total parameters, and just behind Qwen3.6 27B (Reasoning),

Experimental OpenVINO INT4 conversion of Muse Glimmer 30B that needs development builds of Optimum Intel and OpenVINO.

Artificial Analysis

@ArtificialAnlys

Meta has released Muse Spark 1.3, their fourth Muse Spark model release in five months. Muse Spark 1.3 (max), which is in limited preview for Meta’s partners, scores 62 on the Artificial Analysis Intelligence Index, behind only Claude Fable 5.1 and Claude Opus 5. The variant

Meta Developers session on what Muse Spark's act-on-perception multimodality unlocks across code, physical action and video workflows, plus Muse Voice Transcribe.

Ryan | Intelligence Engineer

@RyanIntEngineer

I just built and validated a complete Muse Glimmer deployment for one DGX Spark. I didn’t make another quant—I integrated the available pieces into a pinned, verified, DFlash-accelerated, tool-capable, reboot-durable stack that actually works in OWUI.

Artificial Analysis puts Muse Spark 1.1 at 51 on its Intelligence Index, 8 points above 1.0, and calls it cost and token efficient versus peers.

Artificial Analysis

@ArtificialAnlys

Last week the Intelligence Index vs Cost Pareto frontier moved out substantially. Claude Fable 5.1, Muse Spark 1.3, and GPT-6 Astra each set a new point in efficient intelligence Link to analysis: artificialanalysis.ai/#intelligence-…

Glimmer obtient 92 % du score d'intelligence de Qwen3.6 (35/38), mais Qwen a généré environ 2,9× plus de tokens sur l'ensemble de l'Intelligence Index. Et sur les endpoints mesurés par Artificial Analysis, Glimmer génère environ 1,8× plus vite. Et le context de glimmer et bien plus efficace ! C est une belle avancer architecture tout de meme , je pense que si il sorte une version 1.1 (surtout pour améliorer terminal benchmark ) ont pourrai être très surpris !

Built a small bridge so Muse can act on my Mac from my phone, and recorded a real session: it looks at the Terminal, reports the epoch, loss and accuracy it sees, then locks the machine when asked. What struck me building it is how much of the work is permissions, not intelligence: per-action consent, small window captures instead of a live feed, rejecting stale observations before any input. Free beta if anyone wants to try it. Developer here, ask away. try wand here today