LLM Comparison

GPT-6.1 Terra vs Gemini 3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Terra vs Gemini 3.1 Pro 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 #125) and wins 2 of 3 shared benchmarks; GPT-6.1 Terra costs less ($1.00/$5.00 vs $2.00/$12.0 per 1M tokens).

Rank #35 vs #125AskClash overall scores 61.7 vs 40.7.
Pricing $1.00/$5.00 vs $2.00/$12.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Google.

GPT-6.1 Terra vs Gemini 3.1 Pro benchmark comparison

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

MetricGPT-6.1 TerraGemini 3.1 Pro
Overall Score61.740.7
Leaderboard Rank#35#125
ACB62.1—
HLE46.251.4
GPQA—94.3
SWE-bench—80.6
SWE-Pro—54.2
Terminal-Bench55.6—
DeepSWE—11.7
GDPval-AA1467.61317.0
MCP Atlas—69.2
Finance Agent—43.0
CharXiv—80.2
MMMU-Pro84.783.9
ARC-AGI 2—77.1
Tau2—99.3
MRCR—84.9
Input Price (per 1M tokens)$1.00$2.00
Output Price (per 1M tokens)$5.00$12.0
Context Window1.05M1M
Benchmarks Published810

GPT-6.1 Terra vs Gemini 3.1 Pro head-to-head charts

GPT-6.1 Terra leads 3 and Gemini 3.1 Pro leads 1 of 4 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 TerraGemini 3.1 Pro
Overall
61.7GPT-6.1 Terra
40.7Gemini 3.1 Pro
HLE
46.2GPT-6.1 Terra
51.4Gemini 3.1 Pro
GDPval-AA
1467.6GPT-6.1 Terra
1317.0Gemini 3.1 Pro
MMMU-Pro
84.7GPT-6.1 Terra
83.9Gemini 3.1 Pro
GPT-6.1 Terra
Input$1.00
Output$5.00
Workload$2.00
Context1.05M
Gemini 3.1 Pro
Input$2.00
Output$12.0
Workload$4.40
Context1M

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

More GPT-6.1 Terra and Gemini 3.1 Pro comparisons

Explore how GPT-6.1 Terra and Gemini 3.1 Pro 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.