AI Model Release Tracker

Muse GlimmerOpen Weight

Released

Muse Glimmer is an AI model released by Meta on Monday, Aug 10 2026, 5 days after Muse Spark 1.2. It is an open-weight model — the trained weights are available to download and run. It is a 30B parameterThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. model with a 128k token context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider.. Benchmark results (shown below) cover Humanity's Last Exam, SWE-Bench Pro, SWE-Bench Verified, Terminal-Bench 2.1, MCP Atlas, DeepSearchQA, and 6 more.

Available from

DeepInfra$0.30$1.20128Kbf16
USD per 1M tokensEvery price here is for one million tokens. A token is roughly three-quarters of a word, so a million tokens is about 750,000 words of text.Checked November 9, 2026Third-party rates from openrouter.ai, not the lab’s own list price.

Benchmarks

Coding

SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better.
51.2%
#37 of 42
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better.
76%
#31 of 79

Terminal & CLI

Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better.
51.7%
#37 of 39

Agentic & tool use

MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better.
75.5%
#12 of 16
DeepSearchQAAgentic browsing — Questions that cannot be answered from one page: the AI has to search the web, follow the trail across several sources, and put the pieces together into an answer. Higher is better.
74.6%
#3 of 3
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better.
65.9%
#22 of 32

Reasoning & science

Humanity's Last ExamMultidisciplinary reasoning — accuracy on the 2,158 text-only questions without tools
22%text only, no tools
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better.
83.5%
#45 of 100
IFBenchInstruction following — Tests whether the AI can follow detailed instructions and satisfy multiple constraints at once. Higher is better.
77%
#3 of 4

Knowledge work

GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo)
953
#24 of 25

Multimodal

CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better.
78.8%
#20 of 28
MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better.
74%
#24 of 29

Compare Muse Glimmer with

Muse Glimmer

Suggested comparisons

Muse GlimmervsMuse EmberMuse GlimmervsGPT-6.1 TerraMuse GlimmervsClaude Fable 5.2Muse GlimmervsGemini 4 CarbonMuse GlimmervsGrok 4.7Muse GlimmervsDeepSeek-V4.1-Flash-1017Muse GlimmervsMistral Large 4Muse GlimmervsKimi K3.1 ProMuse GlimmervsGLM-5.3-FlashMuse GlimmervsQwen3.8-Max-0902Muse GlimmervsNemotron 3.5 Bolt E4B 4GB

About

Muse Glimmer was introduced on August 10, 2026 as Meta's 30-billion-parameter model for local agent workflows. Meta released the weights under Apache 2.0 and emphasized tool calling, local coding and running assistants on user-controlled hardware. The model's compact size was chosen around the memory and computation constraints of those deployments.

The release included a model card and deployment guidance, with optimized software integrations following separately. Local operation could keep model inference on the user's device, while any connected tools or external services still determined what information left it. Glimmer was a distinct deployment option from the hosted Muse Spark models. Muse Ember, announced on November 9, 2026, is a hosted API model for high-volume work and was not released as weights.

Frequently asked questions

Muse Glimmer was released by Meta on Monday, Aug 10 2026.

All Meta releases

19 tracked