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Model comparison

LFM2.5-230M vs Muse Spark 1.1

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
LiquidAI
N/A
No comparison
77.44/100
0 category wins1 category wins

Public leaderboard positions: LFM2.5-230M unranked (Not scored); Muse Spark 1.1 #6 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. LFM2.5-230M and Muse Spark 1.1 share 0 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to LFM2.5-230M; 39 to Muse Spark 1.1.

Updated July 23, 2026
Shared results
0
LFM2.5-230M only
6
Muse Spark 1.1 only
39
Comparable categories
1 / 8

Treat this as a split decision. LFM2.5-230M makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Muse Spark 1.1 is the better fit if knowledge is the priority or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

LFM2.5-230M and Muse Spark 1.1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Muse Spark 1.1 is the reasoning model in the pair, while LFM2.5-230M is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Muse Spark 1.1 gives you the larger context window at 1M, compared with 32K for LFM2.5-230M.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricLFM2.5-230MMuse Spark 1.1Comparison
Input / output priceUSD per 1M tokensLFM2.5-230M$0 input / $0 outputMuse Spark 1.1Not availableA complete price comparison is not available.
Generation speedtokens per secondLFM2.5-230MNot availableMuse Spark 1.1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLFM2.5-230MNot availableMuse Spark 1.1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensLFM2.5-230M32KMuse Spark 1.11MMuse Spark 1.1 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLFM2.5-230MMuse Spark 1.1Result
BFCL v4Source 21.0%Not comparable
Terminal-Bench 2.0Source 80%Not comparable
MCP AtlasSource 88.1%Not comparable
ToolathlonSource 75.6%Not comparable
OSWorld-VerifiedSource 80.8%Not comparable
DeepSearchQASource 84.9%Not comparable
CyberGymSource 59.0%Not comparable
Finance Agent v2Source 57.2%Not comparable
deepSweSource 53.3%Not comparable
OSWorld 2.0Source 14.2%Not comparable
JobBenchSource 54.7%Not comparable
CybenchSource 92.9%Not comparable
ExploitGymSource 0.8%Not comparable
AA Agentic IndexSource 37.5%Not comparable
GDPval-AASource 43.7%Not comparable
GDPval-AASource 1374Not comparable
AA BriefcaseSource 863Not comparable
AA AutomationBenchSource 42.8%Not comparable
AA Harvey LABSource 93.1%Not comparable
AA Tau3 BankingSource 25.2%Not comparable
aaTerminalBench21Source 77.9%Not comparable
Coding
BenchmarkLFM2.5-230MMuse Spark 1.1Result
Terminal-Bench 2.0Source 80.0%Not comparable
SWE-bench ProSource 61.5%Not comparable
AA Coding IndexSource 71.3%Not comparable
AA-SciCodeSource 58.2%Not comparable
Reasoning
BenchmarkLFM2.5-230MMuse Spark 1.1Result
MRCR 1MSource 54.1%Not comparable
AA-LCRSource 63.3%Not comparable
CritPtSource 15.1%Not comparable
KnowledgeMuse Spark 1.1 wins
BenchmarkLFM2.5-230MMuse Spark 1.1Result
GPQASource 25.4%Not comparable
GPQA-DSource 25.4%Not comparable
MMLU-ProSource 20.3%Not comparable
HLESource 62.1%Not comparable
HLE w/o toolsSource 52.2%Not comparable
HealthBench ProfessionalSource 59.3%Not comparable
Artificial Analysis Intelligence IndexSource 50.6%Not comparable
AA-GPQA DiamondSource 89.8%Not comparable
AA-HLESource 45.1%Not comparable
AA-Omniscience IndexSource 18.0%Not comparable
AA-Omniscience AccuracySource 40.6%Not comparable
AA-Omniscience Hallucination RateSource 38.1%Not comparable
Multimodal
BenchmarkLFM2.5-230MMuse Spark 1.1Result
CharXivSource 88.4%Not comparable
BabyVisionSource 76.3%Not comparable
Design Arena WebsiteSource 1299Not comparable
Inst. Following
BenchmarkLFM2.5-230MMuse Spark 1.1Result
IFEvalSource 71.7%Not comparable
IFBenchSource 38.4%Not comparable
Frequently Asked Questions (2)

Which is better, LFM2.5-230M or Muse Spark 1.1?

LFM2.5-230M and Muse Spark 1.1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, LFM2.5-230M or Muse Spark 1.1?

Muse Spark 1.1 has the edge for knowledge tasks in this comparison, averaging 62.1 versus 21.2. LFM2.5-230M stays close enough that the answer can still flip depending on your workload.

Related Comparisons

Last updated: July 23, 2026

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