LLM Comparison

GPT-6.1 Terra vs Gemini 3.6 Flash: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Terra vs Gemini 3.6 Flash 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 #129) and wins 4 of 4 shared benchmarks; GPT-6.1 Terra costs less ($1.00/$5.00 vs $1.50/$7.50 per 1M tokens).

Rank #35 vs #129AskClash overall scores 61.7 vs 44.7.
Pricing $1.00/$5.00 vs $1.50/$7.50Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Google.

GPT-6.1 Terra vs Gemini 3.6 Flash benchmark comparison

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

MetricGPT-6.1 TerraGemini 3.6 Flash
Overall Score61.744.7
Leaderboard Rank#35#129
ACB62.133.8
HLE46.238.0
GPQA—92.8
SWE-Pro—58.7
Terminal-Bench55.6—
DeepSWE—46.7
GDPval-AA1467.61421.0
OSWorld—83.0
CharXiv—85.2
MMMU-Pro84.783.2
MRCR—91.8
Input Price (per 1M tokens)$1.00$1.50
Output Price (per 1M tokens)$5.00$7.50
Context Window1.05M1M
Benchmarks Published89

GPT-6.1 Terra vs Gemini 3.6 Flash head-to-head charts

GPT-6.1 Terra leads 5 and Gemini 3.6 Flash leads 0 of 5 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 3.6 Flash
Overall
61.7GPT-6.1 Terra
44.7Gemini 3.6 Flash
ACB
62.1GPT-6.1 Terra
33.8Gemini 3.6 Flash
HLE
46.2GPT-6.1 Terra
38.0Gemini 3.6 Flash
GDPval-AA
1467.6GPT-6.1 Terra
1421.0Gemini 3.6 Flash
MMMU-Pro
84.7GPT-6.1 Terra
83.2Gemini 3.6 Flash
GPT-6.1 Terra
Input$1.00
Output$5.00
Workload$2.00
Context1.05M
Gemini 3.6 Flash
Input$1.50
Output$7.50
Workload$3.00
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 3.6 Flash comparisons

Explore how GPT-6.1 Terra and Gemini 3.6 Flash 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.