Gemini 3.0 FlashvsMuse Spark
Gemini 3.0 Flash | Muse Spark | |
|---|---|---|
| Benchmarks | ||
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. | 49.6% | 55% |
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. | 78% | 77.4% |
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. | 58% | 67.3% |
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. | 62% | 82.2% |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | 33.6% | 42.5% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 90.4% | 89.5% |
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. | 65.1% | 53.3% |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | 80.3% | 88.9% |
| BenchmarksPublished by one model only | ||
Gray Swan IPI · k = 1Prompt injection robustness — Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. Gray Swan's indirect prompt injection benchmark measures how often such an attack succeeds when the attacker gets a single try. Lower is better. | — | 2.9% |
Gray Swan IPI · k = 10Prompt injection robustness — Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 10 tries and counts an attack as successful if any of them works. Lower is better. | — | 14.3% |
Gray Swan IPI · k = 15Prompt injection robustness — Attackers hide malicious instructions inside content the AI reads — a web page, an email, a document — and try to hijack what it does. This variant gives the attacker 15 tries and counts an attack as successful if any of them works. Lower is better. | — | 16.5% |
DeepSWE 1.1Agentic coding — Artificial 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. | — | 10% |
JobBenchProfessional tool use — Tests the AI on professional workplace tasks that require using real work tools — the kind of multi-step jobs an office worker handles. Higher is better. | — | 17% |
Toolathlon-VerifiedPersonal tool use — Tests how well the AI uses everyday personal tools and apps to get things done — a human-checked version of Toolathlon. Higher is better. | — | 49.4% |
ToolathlonGeneral tool use — Tests how well the AI uses everyday real-world tools and apps to get things done. Higher is better. | 49.4% | — |
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. | 33.7% | — |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity'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. | — | 50.4% |
Finance Agent v2Agentic financial analysis — Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 42.6% | — |
GDPval-AAKnowledge work — Measures how well the AI does economically valuable knowledge work, judged against human experts. Shown as a rating (like a chess Elo) — higher is better. | 1204 | — |
BabyVisionVisual reasoning — Tests core visual reasoning — seeing and understanding images the way even young children can, which AIs often find surprisingly hard. Higher is better. | — | 39.9% |
MMMU-ProMultimodal reasoning — A tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 81.2% | — |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | — | 80.4% |
Blueprint-Bench 2Spatial reasoning — Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better. | 0% | — |
MRCR v2 (8-needle) · 128k averageLong context — Tests whether the AI can find specific details buried inside a very long document (around 128k tokens — roughly a long book). Higher is better. | 67.2% | — |
MRCR v2 (8-needle) · 1M pointwiseLong context — Tests whether the AI can find specific details buried inside an enormous document (around 1 million tokens — many books). Higher is better. | 22.1% | — |
| Overview | ||
| Company | Meta | |
| Release date | Dec 17 2025 | Apr 8 2026 |
| Access | Proprietary | Proprietary |
Other comparisons
Gemini 3.0 FlashvsClaude Opus 5Muse SparkvsClaude Opus 5Gemini 3.0 FlashvsGPT-5.6 SolMuse SparkvsGPT-5.6 SolGemini 3.0 FlashvsGrok 4.6Muse SparkvsGrok 4.6Gemini 3.0 FlashvsDeepSeek-V4-Pro-0813Muse SparkvsDeepSeek-V4-Pro-0813Gemini 3.0 FlashvsMistral Medium 3.5Muse SparkvsMistral Medium 3.5Gemini 3.0 FlashvsKimi K3Muse SparkvsKimi K3
Frequently asked questions
Muse Spark leads Gemini 3.0 Flash on 5 of the 8 benchmarks they both report. Gemini 3.0 Flash shipped 112 days before Muse Spark, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On SWE-Bench Pro, Muse Spark leads at 55% vs Gemini 3.0 Flash at 49.6%. On SWE-Bench Verified, Gemini 3.0 Flash leads at 78% vs Muse Spark at 77.4%. On Terminal-Bench 2.1, Muse Spark leads at 67.3% vs Gemini 3.0 Flash at 58%. On MCP Atlas, Muse Spark leads at 82.2% vs Gemini 3.0 Flash at 62%. On ARC-AGI-2, Muse Spark leads at 42.5% vs Gemini 3.0 Flash at 33.6%. On GPQA Diamond, Gemini 3.0 Flash leads at 90.4% vs Muse Spark at 89.5%. On OSWorld-Verified, Gemini 3.0 Flash leads at 65.1% vs Muse Spark at 53.3%. On CharXiv Reasoning, Muse Spark leads at 88.9% vs Gemini 3.0 Flash at 80.3%.
Gemini 3.0 Flash was released by Google on Dec 17 2025.
Muse Spark was released by Meta on Apr 8 2026.
Muse Spark leads on SWE-Bench Pro — Gemini 3.0 Flash 49.6% vs Muse Spark 55%.
Muse Spark leads on ARC-AGI-2 — Gemini 3.0 Flash 33.6% vs Muse Spark 42.5%.