Compare · ModelsLive · 2 picked · head to head
Gemini 3 Pro vs Muse Spark
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Gemini 3 Pro wins on 6/11 benchmarks
Gemini 3 Pro wins 6 of 11 shared benchmarks. Leads in math · knowledge · general.
Category leads
speed·Muse Sparkarena·Muse Sparkmath·Gemini 3 Proknowledge·Gemini 3 Progeneral·Gemini 3 Pro
Hype vs Reality
Attention vs performance
Gemini 3 Pro
#71 by perf·#6 by attention
Muse Spark
#74 by perf·no signal
Vendor risk
Who is behind the model
Google DeepMind
$4.20T·Tier 1
U
Unknown
private · undisclosed
Head to head
11 benchmarks · 2 models
Gemini 3 ProMuse Spark
Artificial Analysis · Agentic Index
Gemini 3 Pro leads by +16.4
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
Gemini 3 Pro
45.0
Muse Spark
28.7
Artificial Analysis · Coding Index
Muse Spark leads by +19.3
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
Gemini 3 Pro
39.4
Muse Spark
58.6
Artificial Analysis · Quality Index
Muse Spark leads by +1.8
Gemini 3 Pro
41.3
Muse Spark
43.1
Chatbot Arena Elo · Overall
Muse Spark leads by +3.9
Gemini 3 Pro
1485.5
Muse Spark
1489.3
FrontierMath-2025-02-28-Private
Muse Spark leads by +2.5
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Gemini 3 Pro
66.0
Muse Spark
68.4
FrontierMath-Tier-4-2025-07-01-Private
Gemini 3 Pro leads by +6.9
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Gemini 3 Pro
31.3
Muse Spark
24.3
GPQA diamond
Gemini 3 Pro leads by +3.8
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Gemini 3 Pro
90.2
Muse Spark
86.4
HLE
Muse Spark leads by +3.2
HLE (Humanity's Last Exam) · a reasoning benchmark designed to be the hardest public evaluation of AI. Questions span mathematics, physics, philosophy, and logic · curated to be at or beyond the frontier of human expert capability. Tested with and without tool augmentation. Claude Opus 4.7 scores 46.9% without tools and 54.7% with tools · making it one of the few benchmarks where the top score is below 60%.
Gemini 3 Pro
34.4
Muse Spark
37.6
OTIS Mock AIME 2024-2025
Gemini 3 Pro leads by +2.5
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3 Pro
91.4
Muse Spark
88.9
Proofbench
Gemini 3 Pro leads by +3.0
Gemini 3 Pro
20.0
Muse Spark
17.0
SimpleQA Verified
Gemini 3 Pro leads by +6.6
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Gemini 3 Pro
72.9
Muse Spark
66.3
Full benchmark table
| Benchmark | Gemini 3 Pro | Muse Spark |
|---|---|---|
Artificial Analysis · Agentic Index Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?" | 45.0 | 28.7 |
Artificial Analysis · Coding Index Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads. | 39.4 | 58.6 |
Artificial Analysis · Quality Index | 41.3 | 43.1 |
Chatbot Arena Elo · Overall | 1485.5 | 1489.3 |
FrontierMath-2025-02-28-Private FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning. | 66.0 | 68.4 |
FrontierMath-Tier-4-2025-07-01-Private FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning. | 31.3 | 24.3 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 90.2 | 86.4 |
HLE HLE (Humanity's Last Exam) · a reasoning benchmark designed to be the hardest public evaluation of AI. Questions span mathematics, physics, philosophy, and logic · curated to be at or beyond the frontier of human expert capability. Tested with and without tool augmentation. Claude Opus 4.7 scores 46.9% without tools and 54.7% with tools · making it one of the few benchmarks where the top score is below 60%. | 34.4 | 37.6 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 91.4 | 88.9 |
Proofbench | 20.0 | 17.0 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 72.9 | 66.3 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| — | — | — | — | |
U Muse Spark | — | — | — | — |