LLM Comparison

GPT-6.1 Terra vs GPT-6 Sol: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Terra vs GPT-6 Sol 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: GPT-6.1 Terra ranks higher (#35 vs #60) and wins 3 of 5 shared benchmarks; GPT-6.1 Terra costs less ($1.00/$5.00 vs $2.00/$10.0 per 1M tokens).

Rank #35 vs #60AskClash overall scores 61.7 vs 57.5.
Pricing $1.00/$5.00 vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs OpenAI.

GPT-6.1 Terra vs GPT-6 Sol benchmark comparison

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

MetricGPT-6.1 TerraGPT-6 Sol
Overall Score61.757.5
Leaderboard Rank#35#60
ACB62.155.8
HLE46.247.9
Terminal-Bench55.643.9
DeepSWE—68.8
GDPval-AA1467.61508.6
Finance Agent—49.0
MMMU-Pro84.782.9
Input Price (per 1M tokens)$1.00$2.00
Output Price (per 1M tokens)$5.00$10.0
Context Window1.05M1.05M
Benchmarks Published810

GPT-6.1 Terra vs GPT-6 Sol head-to-head charts

GPT-6.1 Terra leads 4 and GPT-6 Sol leads 2 of 6 shared benchmarks. GPT-6.1 Terra is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-6.1 TerraGPT-6 Sol
Overall
61.7GPT-6.1 Terra
57.5GPT-6 Sol
ACB
62.1GPT-6.1 Terra
55.8GPT-6 Sol
HLE
46.2GPT-6.1 Terra
47.9GPT-6 Sol
Terminal-Bench
55.6GPT-6.1 Terra
43.9GPT-6 Sol
GDPval-AA
1467.6GPT-6.1 Terra
1508.6GPT-6 Sol
MMMU-Pro
84.7GPT-6.1 Terra
82.9GPT-6 Sol
GPT-6.1 Terra
Input$1.00
Output$5.00
Workload$2.00
Context1.05M
GPT-6 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M

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

More GPT-6.1 Terra and GPT-6 Sol comparisons

Explore how GPT-6.1 Terra and GPT-6 Sol 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.