LLM Comparison

Muse Spark 1.1 vs DeepSeek V4 Flash 0731: benchmark scores, pricing & comparison.

Side-by-side Muse Spark 1.1 vs DeepSeek V4 Flash 0731 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #7 vs #16AskClash overall scores 72.9 vs 56.1.
Pricing $1.25/$4.25 vs $0.14/$0.28Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightMeta vs DeepSeek.

Muse Spark 1.1 vs DeepSeek V4 Flash 0731 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricMuse Spark 1.1DeepSeek V4 Flash 0731
Overall Score72.956.1
Leaderboard Rank#7#16
RWT7.5
HLE62.137.0
GPQA91.0
MATH-50057.4
SWE-bench79.0
SWE-Pro61.5
Terminal-Bench80.082.7
DeepSWE54.4
OSWorld80.8
MCP Atlas88.169.0
Finance Agent57.2
CharXiv88.4
MRCR54.178.7
Input Price (per 1M tokens)$1.25$0.14
Output Price (per 1M tokens)$4.25$0.28
Context Window1M1M
Benchmarks Published109

Muse Spark 1.1 vs DeepSeek V4 Flash 0731 head-to-head charts

Muse Spark 1.1 leads 3 and DeepSeek V4 Flash 0731 leads 2 of 5 shared benchmarks. DeepSeek V4 Flash 0731 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Muse Spark 1.1DeepSeek V4 Flash 0731
Overall
72.9Muse Spark 1.1
56.1DeepSeek V4 Flash 0731
HLE
62.1Muse Spark 1.1
37.0DeepSeek V4 Flash 0731
Terminal-Bench
80.0Muse Spark 1.1
82.7DeepSeek V4 Flash 0731
MCP Atlas
88.1Muse Spark 1.1
69.0DeepSeek V4 Flash 0731
MRCR
54.1Muse Spark 1.1
78.7DeepSeek V4 Flash 0731
Muse Spark 1.1
Input$1.25
Output$4.25
Workload$2.10
Context1M
DeepSeek V4 Flash 0731
Input$0.14
Output$0.28
Workload$0.20
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More Muse Spark 1.1 and DeepSeek V4 Flash 0731 comparisons

Explore how Muse Spark 1.1 and DeepSeek V4 Flash 0731 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.