Muse GlimmervsQwen3.5
Muse Glimmer | Qwen3.5 | |
|---|---|---|
| Specifications | ||
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one. | 30B | 397B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | — | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.60 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $3.60 |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $0.30DeepInfra | $0.08Darkbloom |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $1.10Phala | $0.13Darkbloom |
| Benchmarks | ||
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% | 76.4% |
Humanity's Last Exam · no toolsMultidisciplinary reasoning — Humanity'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% | 28.7% |
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% | 88.4% |
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% | 62.2% |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | 78.8% | 80.8% |
MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 74% | 79% |
| BenchmarksPublished by one model only | ||
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% | — |
SWE-Bench MultilingualMultilingual coding — Like SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | — | 69.3% |
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% | — |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | — | 52.5% |
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% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 69% |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 953 | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | — | 85% |
| Overview | ||
| Company | Meta | Qwen |
| Release date | Aug 10 2026 | Feb 16 2026 |
| Access | Open Weight | Open Weight |
Other comparisons
Muse GlimmervsClaude Fable 5.1Qwen3.5vsClaude Fable 5.1Muse GlimmervsGPT-6 AstraQwen3.5vsGPT-6 AstraMuse GlimmervsGemini 3.8 FlashQwen3.5vsGemini 3.8 FlashMuse GlimmervsGrok 4.6Qwen3.5vsGrok 4.6Muse GlimmervsDeepSeek-V4.1-FlashQwen3.5vsDeepSeek-V4.1-FlashMuse GlimmervsMistral Medium 3.5Qwen3.5vsMistral Medium 3.5
Frequently asked questions
Qwen3.5 leads Muse Glimmer on 5 of the 6 benchmarks they both report. Only Qwen3.5 has a verified first-party API price: $0.60 per million input tokens and $3.60 per million output tokens. No pay-as-you-go API rate is tracked for Muse Glimmer. Qwen3.5 shipped 175 days before Muse Glimmer, so benchmark comparisons should account for the intervening progress.
Muse Glimmer has 30B parameters, while Qwen3.5 has 397B.
On SWE-Bench Verified, Qwen3.5 leads at 76.4% vs Muse Glimmer at 76%. On Humanity's Last Exam · no tools, Qwen3.5 leads at 28.7% vs Muse Glimmer at 22%. On GPQA Diamond, Qwen3.5 leads at 88.4% vs Muse Glimmer at 83.5%. On OSWorld-Verified, Muse Glimmer leads at 65.9% vs Qwen3.5 at 62.2%. On CharXiv Reasoning, Qwen3.5 leads at 80.8% vs Muse Glimmer at 78.8%. On MMMU-Pro, Qwen3.5 leads at 79% vs Muse Glimmer at 74%.