Muse GlimmervsGLM-5.2
Muse Glimmer | GLM-5.2 | |
|---|---|---|
| Specifications | ||
Parameters | 30B | 744B |
Context window | — | 1M |
| Benchmarks | ||
Nonsense detection BullshitBench v2Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 31% |
Agentic coding SWE-Bench ProCan 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% | 62.1%Best |
Coding SWE-Bench VerifiedReal 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% | — |
Agentic coding CursorBench v3.2Cursor's own test of harder, real-world coding tasks inside a code editor, on the refreshed v3.2 task set. Scores aren't comparable with v3.1. Higher is better. | — | 55% |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | — | 54.6% |
Agentic coding DeepSWE 1.1Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 44% |
Next.js coding Next.js EvalsVercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 88% |
Agentic computer work Frontier-Bench v0.1A hard, ever-evolving set of real computer tasks — coding, system administration, data work, and more — that an AI agent has to complete on its own. Run by the Harbor / Laude Institute team as the successor to Terminal-Bench (v0.1 is the first release of the task set). The score is the share of tasks solved. Higher is better. | — | 5.1% |
Agentic terminal coding Terminal-Bench 2.1Can 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% | 81%Best |
Multi-step tool use MCP AtlasCan 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% | — |
Multidisciplinary reasoning Humanity's Last Exam · no toolsHumanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | 22% | 40.5%Best |
Multidisciplinary reasoning Humanity's Last Exam · with toolsHumanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 54.7% |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 83.5% | 91.2%Best |
Agentic computer use OSWorld-VerifiedCan the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 65.9% | — |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | 953 | 1514Best |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | 78.8% | — |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 74% | — |
Community preference (code) Arena Elo (Code)Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | — | 1587 |
| Overview | ||
| Company | Meta | Z.ai |
| Release date | Aug 10 2026 | Jun 16 2026 |
| Access | Open Weight | Open Weight |
Which is better: Muse Glimmer or GLM-5.2?
GLM-5.2 leads Muse Glimmer on 5 of the 5 benchmarks they both report. GLM-5.2 shipped 55 days before Muse Glimmer, so benchmark comparisons should account for the intervening progress.
Muse Glimmer has 30B parameters, while GLM-5.2 has 744B.
On SWE-Bench Pro, GLM-5.2 leads at 62.1% vs Muse Glimmer at 51.2%. On Terminal-Bench 2.1, GLM-5.2 leads at 81% vs Muse Glimmer at 51.7%. On Humanity's Last Exam · no tools, GLM-5.2 leads at 40.5% vs Muse Glimmer at 22%. On GPQA Diamond, GLM-5.2 leads at 91.2% vs Muse Glimmer at 83.5%. On GDPval-AA v2, GLM-5.2 leads at 1514 vs Muse Glimmer at 953.
Frequently asked questions
Muse Glimmer was released by Meta on Aug 10 2026.
GLM-5.2 was released by Z.ai on Jun 16 2026.
GLM-5.2 leads on SWE-Bench Pro — Muse Glimmer 51.2% vs GLM-5.2 62.1%.
GLM-5.2 leads on Humanity's Last Exam · no tools — Muse Glimmer 22% vs GLM-5.2 40.5%.
Other comparisons
Muse GlimmervsClaude Opus 5GLM-5.2vsClaude Opus 5Muse GlimmervsGPT-5.6 SolGLM-5.2vsGPT-5.6 SolMuse GlimmervsGemini 3.6 FlashGLM-5.2vsGemini 3.6 FlashMuse GlimmervsGrok 4.5GLM-5.2vsGrok 4.5Muse GlimmervsDeepSeek-V4-Flash-0731GLM-5.2vsDeepSeek-V4-Flash-0731Muse GlimmervsMistral Medium 3.5GLM-5.2vsMistral Medium 3.5