Which is better: GPT-6.1 Terra or Gemini 3.7 Flash?

Verdict: GPT-6.1 Terra ranks higher (#35 vs #95); Gemini 3.7 Flash wins 3 of 4 shared benchmarks; GPT-6.1 Terra costs less ($1.00/$5.00 vs $1.50/$7.50 per 1M tokens). AskClash compares GPT-6.1 Terra and Gemini 3.7 Flash side by side across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, AskClash ACB, and context window so you can see which model wins on each benchmark.

How do GPT-6.1 Terra and Gemini 3.7 Flash compare on coding benchmarks?

The comparison table shows SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, DeepSWE, and coding agent index scores for both GPT-6.1 Terra and Gemini 3.7 Flash when publicly disclosed.

LLM Comparison

GPT-6.1 Terra vs Gemini 3.7 Flash: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Terra vs Gemini 3.7 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 #95); Gemini 3.7 Flash wins 3 of 4 shared benchmarks; GPT-6.1 Terra costs less ($1.00/$5.00 vs $1.50/$7.50 per 1M tokens).

Open live leaderboard GPT-6.1 Terra model page Gemini 3.7 Flash model page

Rank #35 vs #95AskClash overall scores 61.7 vs 51.6.

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 3.7 Flash benchmark comparison

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

Metric	GPT-6.1 Terra	Gemini 3.7 Flash
Overall Score	61.7	51.6
Leaderboard Rank	#35	#95
ACB	62.1	38.9
HLE	46.2	53.6
GPQA	—	94.5
Terminal-Bench	55.6	—
DeepSWE	—	65.3
GDPval-AA	1467.6	1525.0
Finance Agent	—	59.0
CharXiv	—	84.5
MMMU-Pro	84.7	85.5
MRCR	—	97.0
Input Price (per 1M tokens)	$1.00	$1.50
Output Price (per 1M tokens)	$5.00	$7.50
Context Window	1.05M	1M
Benchmarks Published	8	11

GPT-6.1 Terra vs Gemini 3.7 Flash head-to-head charts

GPT-6.1 Terra leads 2 and Gemini 3.7 Flash leads 3 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 3.7 Flash

Overall

61.7GPT-6.1 Terra

51.6Gemini 3.7 Flash

ACB

62.1GPT-6.1 Terra

38.9Gemini 3.7 Flash

HLE

46.2GPT-6.1 Terra

53.6Gemini 3.7 Flash

GDPval-AA

1467.6GPT-6.1 Terra

1525.0Gemini 3.7 Flash

MMMU-Pro

84.7GPT-6.1 Terra

85.5Gemini 3.7 Flash

GPT-6.1 Terra

Input$1.00

Output$5.00

Workload$2.00

Context1.05M

Gemini 3.7 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 3.7 Flash comparisons

Explore how GPT-6.1 Terra and Gemini 3.7 Flash stack up against other top-ranked LLMs.

Kimi K3.1 Pro vs GPT-6.1 Terra Kimi K3.1 Pro vs Gemini 3.7 Flash Claude Opus 5.5 vs GPT-6.1 Terra Claude Opus 5.5 vs Gemini 3.7 Flash Claude Fable 5.1 vs GPT-6.1 Terra Claude Fable 5.1 vs Gemini 3.7 Flash Claude Sonnet 5.5 vs GPT-6.1 Terra Claude Sonnet 5.5 vs Gemini 3.7 Flash Claude Opus 5 vs GPT-6.1 Terra Claude Opus 5 vs Gemini 3.7 Flash

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.