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Model comparison

Llama 3.1 405B vs Muse Spark

Data verified

Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

51.71/100
Margin
19.3pts
winning →
71.04/100
0 category wins0 category wins

Public leaderboard positions: Llama 3.1 405B #102 (Estimated); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Llama 3.1 405B and Muse Spark share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Llama 3.1 405B; 28 to Muse Spark.

Updated July 23, 2026
Shared results
11
Llama 3.1 405B only
0
Muse Spark only
28
Comparable categories
0 / 8

Benchmark data for Llama 3.1 405B and Muse Spark is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Muse Spark has the larger context window at 262K, compared with 128K for Llama 3.1 405B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Llama 3.1 405B and Muse Spark
CategoryLlama 3.1 405BΔMuse Spark
AgenticLlama 3.1 405BNot measuredMarginNo overlapMuse Spark59.0
CodingLlama 3.1 405BNot measuredMarginNo overlapMuse Spark67.8
ReasoningLlama 3.1 405BNot measuredMarginNo overlapMuse Spark42.5
KnowledgeLlama 3.1 405BNot measuredMarginNo overlapMuse Spark50.4
MathLlama 3.1 405BNot measuredMarginNo overlapMuse Spark32.9
MultimodalLlama 3.1 405BNot measuredMarginNo overlapMuse Spark82.5

Operational comparison

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

MetricLlama 3.1 405BMuse SparkComparison
Input / output priceUSD per 1M tokensLlama 3.1 405B$0 input / $0 outputMuse SparkNot availableA complete price comparison is not available.
Generation speedtokens per secondLlama 3.1 405B29 tok/sMuse SparkNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenLlama 3.1 405B2.19 sMuse SparkNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensLlama 3.1 405B128KMuse Spark262KMuse Spark lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkLlama 3.1 405BMuse SparkResult
τ²-bench resultsSource 19%91.5%Muse Spark leads
Terminal-Bench 2.0Source 59%Not comparable
DeepSearchQASource 74.8%Not comparable
CyberGymSource 43.5%Not comparable
Claw-EvalSource 63.8%Not comparable
AA Agentic IndexSource 28.7%Not comparable
GDPval-AASource 32.2%Not comparable
GDPval-AASource 1144Not comparable
Coding
BenchmarkLlama 3.1 405BMuse SparkResult
AA-SciCodeSource 29.9%51.5%Muse Spark leads
SWE-bench VerifiedSource 77.4%Not comparable
SWE-bench ProSource 52.4%Not comparable
LiveCodeBench ProSource 80.0%Not comparable
Vibe Code BenchSource 19.67%Not comparable
AA Coding IndexSource 58.6%Not comparable
Reasoning
BenchmarkLlama 3.1 405BMuse SparkResult
AA-LCRSource 24.3%69.7%Muse Spark leads
CritPtSource 0.0%11.3%Muse Spark leads
ARC-AGI-2Source 42.5%Not comparable
Knowledge
BenchmarkLlama 3.1 405BMuse SparkResult
Artificial Analysis Intelligence IndexSource 8.5%43.1%Muse Spark leads
AA-GPQA DiamondSource 51.5%88.4%Muse Spark leads
AA-HLESource 4.2%39.9%Muse Spark leads
AA-Omniscience IndexSource -17.3%4.1%Muse Spark leads
AA-Omniscience AccuracySource 22.3%44.6%Muse Spark leads
AA-Omniscience Hallucination RateSource 51.0%73.2%Llama 3.1 405B leads
GPQA-DSource 89.5%Not comparable
HLESource 50.4%Not comparable
HLE w/o toolsSource 42.8%Not comparable
HealthBench HardSource 42.8%Not comparable
MedXpertQA (Text)Source 52.6%Not comparable
Math
BenchmarkLlama 3.1 405BMuse SparkResult
FrontierMath v2 (Tiers 1-3)Source 39.000%Not comparable
FrontierMath v2 (Tier 4)Source 14.600%Not comparable
Multimodal
BenchmarkLlama 3.1 405BMuse SparkResult
CharXivSource 86.4%Not comparable
MMMU-ProSource 80.4%Not comparable
ERQASource 64.7%Not comparable
SimpleVQASource 71.3%Not comparable
ScreenSpot ProSource 84.1%Not comparable
ZeroBenchSource 33.0%Not comparable
MedXpertQA (MM)Source 78.4%Not comparable
AA-MMMU-ProSource 80.5%Not comparable
Inst. Following
BenchmarkLlama 3.1 405BMuse SparkResult
AA-IFBenchSource 39.0%75.9%Muse Spark leads
Frequently Asked Questions (3)

Can I compare Llama 3.1 405B and Muse Spark on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Llama 3.1 405B and Muse Spark today?

Llama 3.1 405B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 23, 2026

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