Gemini 3.0 Flash vs Muse Spark
Google Gemini 3.0 Flash | Meta Muse Spark | |
|---|---|---|
| Overview | ||
| Company | Meta | |
| Release date | Dec 17 2025 | Apr 8 2026 |
| Access | Proprietary | Proprietary |
| Benchmarks | ||
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. | 49.6% | 55%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. | 78%Best | 77.4% |
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. | — | 10% |
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. | 58% | 67.3%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. | 62% | 82.2%Best |
Professional tool use JobBenchTests 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% |
Personal tool use Toolathlon-VerifiedTests 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% |
General tool use ToolathlonTests how well the AI uses everyday real-world tools and apps to get things done. Higher is better. | 49.4% | — |
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. | 33.7% | — |
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. | — | 50.4% |
Abstract reasoning ARC-AGI-2Puzzle-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%Best |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 90.4%Best | 89.5% |
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. | 65.1%Best | 53.3% |
Agentic financial analysis Finance Agent v2Tests the AI on real financial-analysis work, like digging through reports and making sound decisions. Higher is better. | 42.6% | — |
Knowledge work GDPval-AAMeasures 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 | — |
Chart reasoning CharXiv ReasoningCan the AI read and reason about complex charts and figures, not just text? Higher is better. | 80.3% | 88.9%Best |
Visual reasoning BabyVisionTests core visual reasoning — seeing and understanding images the way even young children can, which AIs often find surprisingly hard. Higher is better. | — | 39.9% |
Multimodal reasoning MMMU-ProA tougher version of MMMU — college-level questions that mix images, diagrams, and text together. Higher is better. | 81.2% | — |
Multimodal MMMUTests the AI on understanding images and text together across many college subjects. Higher is better. | — | 80.4% |
Spatial reasoning Blueprint-Bench 2Can the AI reason about space and layout — for example, understanding a floor plan or blueprint? Higher is better. | 0% | — |
Long context MRCR v2 (8-needle) · 128k averageTests 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% | — |
Long context MRCR v2 (8-needle) · 1M pointwiseTests whether the AI can find specific details buried inside an enormous document (around 1 million tokens — many books). Higher is better. | 22.1% | — |
Community preference Arena Elo (Text)Real people chat with two anonymous AIs side by side and vote for the answer they prefer. Votes become a chess-style Elo rating on arena.ai — it measures which AI people actually like, not test scores. Higher is better. | — | 1488 |
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. | 1437 | — |
| Timeline | ||
| Release gap | Gemini 3.0 Flash shipped 112 days before Muse Spark | |
Which is better: Gemini 3.0 Flash or Muse Spark?
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%.
Frequently asked questions
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%.
Other comparisons
Gemini 3.0 Flash vs Claude Sonnet 5Muse Spark vs Claude Sonnet 5Gemini 3.0 Flash vs GPT-5.6 SolMuse Spark vs GPT-5.6 SolGemini 3.0 Flash vs Grok 4.5Muse Spark vs Grok 4.5Gemini 3.0 Flash vs DeepSeek-V4-ProMuse Spark vs DeepSeek-V4-ProGemini 3.0 Flash vs Mistral Medium 3.5Muse Spark vs Mistral Medium 3.5Gemini 3.0 Flash vs Kimi K2.7 CodeMuse Spark vs Kimi K2.7 Code