Which is better: GPT-6.1 Sol or MiniMax-M3?

Verdict: GPT-6.1 Sol ranks higher (#30 vs #45) and wins 1 of 1 shared benchmarks; MiniMax-M3 costs less ($0.30/$1.20 vs $2.00/$10.0 per 1M tokens). AskClash compares GPT-6.1 Sol and MiniMax-M3 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 Sol and MiniMax-M3 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 Sol and MiniMax-M3 when publicly disclosed.

LLM Comparison

GPT-6.1 Sol vs MiniMax-M3: benchmark scores, pricing & comparison.

Side-by-side GPT-6.1 Sol vs MiniMax-M3 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 Sol ranks higher (#30 vs #45) and wins 1 of 1 shared benchmarks; MiniMax-M3 costs less ($0.30/$1.20 vs $2.00/$10.0 per 1M tokens).

Open live leaderboard GPT-6.1 Sol model page MiniMax-M3 model page

Rank #30 vs #45AskClash overall scores 58.1 vs 43.0.

Pricing $2.00/$10.0 vs $0.30/$1.20Input and output token prices per 1M tokens when published.

Proprietary vs Open WeightOpenAI vs MiniMax.

GPT-6.1 Sol vs MiniMax-M3 benchmark comparison

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

Metric	GPT-6.1 Sol	MiniMax-M3
Overall Score	58.1	43.0
Leaderboard Rank	#30	#45
ACB	61.9	29.8
RWT	—	8.5
HLE	—	37.1
GPQA	—	92.9
IFEval	—	82.9
SWE-bench	—	80.5
SWE-Pro	—	59.0
Terminal-Bench	—	66.0
DeepSWE	75.2	—
GDPval-AA	—	58.4
OSWorld	—	70.1
MCP Atlas	—	74.2
Finance Agent	—	48.3
MMMU-Pro	—	78.1
Tau2	—	88.9
Input Price (per 1M tokens)	$2.00	$0.30
Output Price (per 1M tokens)	$10.0	$1.20
Context Window	1.05M	1M
Benchmarks Published	3	12

GPT-6.1 Sol vs MiniMax-M3 head-to-head charts

GPT-6.1 Sol leads 2 and MiniMax-M3 leads 0 of 2 shared benchmarks. MiniMax-M3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-6.1 SolMiniMax-M3

Overall

58.1GPT-6.1 Sol

43.0MiniMax-M3

ACB

61.9GPT-6.1 Sol

29.8MiniMax-M3

GPT-6.1 Sol

Input$2.00

Output$10.0

Workload$4.00

Context1.05M

MiniMax-M3

Input$0.30

Output$1.20

Workload$0.54

Context1M

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

More GPT-6.1 Sol and MiniMax-M3 comparisons

Explore how GPT-6.1 Sol and MiniMax-M3 stack up against other top-ranked LLMs.

Claude Fable 5.1 vs GPT-6.1 Sol Claude Fable 5.1 vs MiniMax-M3 Claude Opus 5.5 vs GPT-6.1 Sol Claude Opus 5.5 vs MiniMax-M3 Claude Fable 5 vs GPT-6.1 Sol Claude Fable 5 vs MiniMax-M3 Claude Opus 5 vs GPT-6.1 Sol Claude Opus 5 vs MiniMax-M3 GPT-5.6 Sol vs GPT-6.1 Sol GPT-5.6 Sol vs MiniMax-M3

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.