LLM Comparison

GPT-5.6 Terra vs Muse Spark 1.2: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Terra 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.

Rank #8 vs #12AskClash overall scores 71.8 vs 70.4.
Pricing $2.50/$15.0 vs $1.25/$4.25Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Meta.

GPT-5.6 Terra 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.

MetricGPT-5.6 TerraMuse Spark 1.2
Overall Score71.870.4
Leaderboard Rank#8#12
RWT8.57.5
Coding Agent Index77.0
HLE62.1
GPQA92.9
SWE-Pro63.461.5
SWE-Atlas81.0
Terminal-Bench87.480.0
DeepSWE69.659.0
OSWorld80.8
MCP Atlas82.2
Finance Agent52.457.2
CharXiv88.4
MMMU-Pro80.7
ARC-AGI 283.9
Tau286.3
MRCR89.654.1
Input Price (per 1M tokens)$2.50$1.25
Output Price (per 1M tokens)$15.0$4.25
Context Window1M1M
Benchmarks Published1411

GPT-5.6 Terra vs Muse Spark 1.2 head-to-head charts

GPT-5.6 Terra leads 6 and Muse Spark 1.2 leads 1 of 7 shared benchmarks. Muse Spark 1.2 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 TerraMuse Spark 1.2
Overall
71.8GPT-5.6 Terra
70.4Muse Spark 1.2
RWT
8.5GPT-5.6 Terra
7.5Muse Spark 1.2
SWE-Pro
63.4GPT-5.6 Terra
61.5Muse Spark 1.2
Terminal-Bench
87.4GPT-5.6 Terra
80.0Muse Spark 1.2
DeepSWE
69.6GPT-5.6 Terra
59.0Muse Spark 1.2
Finance Agent
52.4GPT-5.6 Terra
57.2Muse Spark 1.2
MRCR
89.6GPT-5.6 Terra
54.1Muse Spark 1.2
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
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 GPT-5.6 Terra and Muse Spark 1.2 comparisons

Explore how GPT-5.6 Terra 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.