LLM Comparison

Muse Spark 1.1 vs GPT-5.6 Terra: benchmark scores, pricing & comparison.

Side-by-side Muse Spark 1.1 vs GPT-5.6 Terra 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 #6 vs #8AskClash overall scores 77.5 vs 76.3.
Pricing $1.25/$4.25 vs $2.50/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryMeta vs OpenAI.

Muse Spark 1.1 vs GPT-5.6 Terra benchmark comparison

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

MetricMuse Spark 1.1GPT-5.6 Terra
Overall Score77.576.3
Leaderboard Rank#6#8
RWT7.58.5
Coding Agent Index77.0
HLE62.1
GPQA92.9
SWE-Pro61.563.4
SWE-Atlas81.0
Terminal-Bench80.087.4
DeepSWE69.6
OSWorld80.8
MCP Atlas88.1
Finance Agent57.252.4
CharXiv88.4
MMMU-Pro80.7
ARC-AGI 283.9
Tau286.3
MRCR54.189.6
Input Price (per 1M tokens)$1.25$2.50
Output Price (per 1M tokens)$4.25$15.0
Context Window1M1M
Benchmarks Published913

Muse Spark 1.1 vs GPT-5.6 Terra head-to-head charts

Muse Spark 1.1 leads 2 and GPT-5.6 Terra leads 4 of 6 shared benchmarks. Muse Spark 1.1 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Muse Spark 1.1GPT-5.6 Terra
Overall
77.5Muse Spark 1.1
76.3GPT-5.6 Terra
RWT
7.5Muse Spark 1.1
8.5GPT-5.6 Terra
SWE-Pro
61.5Muse Spark 1.1
63.4GPT-5.6 Terra
Terminal-Bench
80.0Muse Spark 1.1
87.4GPT-5.6 Terra
Finance Agent
57.2Muse Spark 1.1
52.4GPT-5.6 Terra
MRCR
54.1Muse Spark 1.1
89.6GPT-5.6 Terra
Muse Spark 1.1
Input$1.25
Output$4.25
Workload$2.10
Context1M
GPT-5.6 Terra
Input$2.50
Output$15.0
Workload$5.50
Context1M

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

More Muse Spark 1.1 and GPT-5.6 Terra comparisons

Explore how Muse Spark 1.1 and GPT-5.6 Terra 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.