LLM Comparison

Kimi K3 vs Muse Spark 1.2: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs Muse Spark 1.2 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.

Verdict: Kimi K3 ranks higher (#34 vs #35) and wins 4 of 4 shared benchmarks; Muse Spark 1.2 costs less ($1.25/$4.25 vs $3.00/$15.0 per 1M tokens).

Rank #34 vs #35AskClash overall scores 50.0 vs 48.6.
Pricing $3.00/$15.0 vs $1.25/$4.25Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryMoonshot AI vs Meta.

Kimi K3 vs Muse Spark 1.2 benchmark comparison

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

MetricKimi K3Muse Spark 1.2
Overall Score50.048.6
Leaderboard Rank#34#35
ACB57.754.8
RWT8.07.5
Coding Agent Index41.4—
HLE43.5—
GPQA93.5—
SWE-Atlas59.9—
Terminal-Bench12.6—
DeepSWE68.559.0
GDPval-AA1668.0—
MCP Atlas84.282.2
Finance Agent60.0—
CharXiv84.8—
MMMU-Pro81.6—
Input Price (per 1M tokens)$3.00$1.25
Output Price (per 1M tokens)$15.0$4.25
Context Window1M1M
Benchmarks Published134

Kimi K3 vs Muse Spark 1.2 head-to-head charts

Kimi K3 leads 5 and Muse Spark 1.2 leads 0 of 5 shared benchmarks. Muse Spark 1.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3Muse Spark 1.2
Overall
50.0Kimi K3
48.6Muse Spark 1.2
ACB
57.7Kimi K3
54.8Muse Spark 1.2
RWT
8.0Kimi K3
7.5Muse Spark 1.2
DeepSWE
68.5Kimi K3
59.0Muse Spark 1.2
MCP Atlas
84.2Kimi K3
82.2Muse Spark 1.2
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
Muse Spark 1.2
Input$1.25
Output$4.25
Workload$2.10
Context1M

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

More Kimi K3 and Muse Spark 1.2 comparisons

Explore how Kimi K3 and Muse Spark 1.2 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.