Muse Spark 1.2vsGLM-5.2
Muse Spark 1.2 | GLM-5.2 | |
|---|---|---|
| Specifications | ||
Parameters | — | 744B |
Context window | 1M | 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. | — | 62.1% |
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. | 59.3%Best | 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. | 82.9%Best | 81% |
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. | — | 40.5% |
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. | — | 91.2% |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | — | 1514 |
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 5 2026 | Jun 16 2026 |
| Access | Proprietary | Open Weight |
Which is better: Muse Spark 1.2 or GLM-5.2?
Muse Spark 1.2 leads GLM-5.2 on 2 of the 2 benchmarks they both report (DeepSWE 1.1, Terminal-Bench 2.1). GLM-5.2 shipped 50 days before Muse Spark 1.2, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Muse Spark 1.2) vs 1M (GLM-5.2). Muse Spark 1.2 is proprietary, while GLM-5.2 is open weight.
On DeepSWE 1.1, Muse Spark 1.2 leads at 59.3% vs GLM-5.2 at 44%. On Terminal-Bench 2.1, Muse Spark 1.2 leads at 82.9% vs GLM-5.2 at 81%.
Frequently asked questions
Muse Spark 1.2 was released by Meta on Aug 5 2026.
GLM-5.2 was released by Z.ai on Jun 16 2026.
Muse Spark 1.2 leads on DeepSWE 1.1 — Muse Spark 1.2 59.3% vs GLM-5.2 44%.
Muse Spark 1.2 has a 1M context window; GLM-5.2 has 1M.
Muse Spark 1.2 is a proprietary model released by Meta. GLM-5.2 is an open weight model released by Z.ai.
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