Claude 3.7 SonnetvsMuse Spark
Claude 3.7 Sonnet | Muse Spark | |
|---|---|---|
| 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. | 62.3% | 77.4% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 68% | 89.5% |
| BenchmarksPublished by one model only | ||
BullshitBench v2Nonsense detection — Given 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. | 49% | — |
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% |
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. | — | 55% |
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% |
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. | — | 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. | — | 82.2% |
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% |
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% |
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. | — | 42.5% |
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. | — | 53.3% |
CharXiv ReasoningChart reasoning — Can the AI read and reason about complex charts and figures, not just text? Higher is better. | — | 88.9% |
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% |
MMMUMultimodal — Tests the AI on understanding images and text together across many college subjects. Higher is better. | — | 80.4% |
| Overview | ||
| Company | Anthropic | Meta |
| Release date | Feb 24 2025 | Apr 8 2026 |
| Access | Proprietary | Proprietary |
Other comparisons
Claude 3.7 SonnetvsGPT-5.6 SolMuse SparkvsGPT-5.6 SolClaude 3.7 SonnetvsGemini 3.7 FlashMuse SparkvsGemini 3.7 FlashClaude 3.7 SonnetvsGrok 4.6Muse SparkvsGrok 4.6Claude 3.7 SonnetvsDeepSeek-V4-Pro-0813Muse SparkvsDeepSeek-V4-Pro-0813Claude 3.7 SonnetvsMistral Medium 3.5Muse SparkvsMistral Medium 3.5Claude 3.7 SonnetvsKimi K3Muse SparkvsKimi K3
Frequently asked questions
Muse Spark leads Claude 3.7 Sonnet on 2 of the 2 benchmarks they both report (SWE-Bench Verified, GPQA Diamond). Claude 3.7 Sonnet shipped 408 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 Verified, Muse Spark leads at 77.4% vs Claude 3.7 Sonnet at 62.3%. On GPQA Diamond, Muse Spark leads at 89.5% vs Claude 3.7 Sonnet at 68%.
Claude 3.7 Sonnet was released by Anthropic on Feb 24 2025.
Muse Spark was released by Meta on Apr 8 2026.
Muse Spark leads on SWE-Bench Verified — Claude 3.7 Sonnet 62.3% vs Muse Spark 77.4%.
Muse Spark leads on GPQA Diamond — Claude 3.7 Sonnet 68% vs Muse Spark 89.5%.