Model comparison

GPT-6.1 Sol vs MiniMax-M2

GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 37.4 on the Noometry Index. MiniMax-M2 costs 7.6× less per token, which makes it the better buy when GPT-6.1 Sol's lead doesn't matter for your workload.

Last verified October 10, 2026. 14 shared benchmarks.

GPT-6.1 Sol OpenAI

65.6

Rank #6 Confirmed

MiniMax-M2

MiniMax

37.4

Rank #204 Confirmed

Summary

They share 14 benchmarks with published results for both. GPT-6.1 Sol scores higher in 9 categories and MiniMax-M2 in 0 categories; 9 gaps are clear of the uncertainty.
The widest gap is in reasoning, where GPT-6.1 Sol leads 81.9 to 19.4.
The biggest single-benchmark swing is NYT Connections (extended): 95.5% for GPT-6.1 Sol and 14.8% for MiniMax-M2.
MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $2 / $10 for GPT-6.1 Sol.
GPT-6.1 Sol accepts more context: 1.05M tokens versus 205K.
MiniMax-M2 has downloadable open weights; the other is API-only.

Side by side

GPT-6.1 Sol and MiniMax-M2 specifications
	GPT-6.1 Sol	MiniMax-M2
Provider	OpenAI	MiniMax
Noometry Index	65.6	37.4
Released	2026-09-29	2025-10-27
Weights	Proprietary	Open
Context window	1.05M	205K
Max output	128K	131K
Input $ / M tokens	$2	$0.30
Output $ / M tokens	$10	$1.20
Results tracked	34	21

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Category by category

Coding GPT-6.1 Sol leads

GPT-6.1 Sol: 63.2 (#8), MiniMax-M2: 39.3 (#159)

Coding benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena WebDev	1755	1297
LMArena Coding	1487	1370
DeepSWE	75.2%	—
FrontierCode	50.2%	—
SWE-bench Verified (bash only)	—	61%
SciCode	55.8%	—

Agentic & Tool Use GPT-6.1 Sol leads

GPT-6.1 Sol: 39.6 (#26), MiniMax-M2: 25.1 (#109)

Agentic & Tool Use benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
Terminal-Bench	—	30%
APEX-Agents	60%	—
GDP.pdf	32%	—
Vending-Bench 2	—	160.6

Reasoning GPT-6.1 Sol leads

GPT-6.1 Sol: 81.9 (#2), MiniMax-M2: 19.4 (#258)

Reasoning benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
NYT Connections (extended)	95.5%	14.8%
LMArena Hard Prompts	1466	1357
ARC-AGI-2	94.2%	—
Kagi LLM Benchmark	—	57.8%
ARC-AGI-1	98.5%	—
CritPt	31.7%	—
Chess Puzzles	61%	—
EBR-Bench	54.3%	—
Mystery Game Puzzles	80%	—
Epoch Capabilities Index	166.09	—

Math GPT-6.1 Sol leads

GPT-6.1 Sol: 93.7 (#1), MiniMax-M2: 37.3 (#160)

Math benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Math	1464	1352
FrontierMath (Tiers 1-3)	93.7%	—
FrontierMath Tier 4	100%	—
OTIS Mock AIME 2024-2025	100%	—
ProofBench	99%	—

Knowledge GPT-6.1 Sol leads

GPT-6.1 Sol: 71.8 (#4), MiniMax-M2: 37.0 (#163)

Knowledge benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Expert	1502	1337
GPQA Diamond	95.4%	—
SimpleQA Verified	73.9%	—

Multimodal Not comparable

GPT-6.1 Sol: 52.7 (#5), MiniMax-M2: —

Multimodal benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Vision	1288	—
Furniture Assembly	80%	—

Multilingual GPT-6.1 Sol leads

GPT-6.1 Sol: 54.3 (#46), MiniMax-M2: 45.3 (#171)

Multilingual benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Non-English	1438	1313
LMArena Chinese	1477	1366
LMArena Russian	1455	1331
LMArena French	—	1335
LMArena German	—	1355
LMArena Spanish	—	1326

Instruction Following GPT-6.1 Sol leads

GPT-6.1 Sol: 77.0 (#29), MiniMax-M2: 70.2 (#166)

Instruction Following benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Instruction Following	1468	1328

Long Context GPT-6.1 Sol leads

GPT-6.1 Sol: 44.9 (#54), MiniMax-M2: 40.5 (#153)

Long Context benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Longer Query	1465	1331

Writing & Preference GPT-6.1 Sol leads

GPT-6.1 Sol: 63.6 (#63), MiniMax-M2: 53.0 (#162)

Writing & Preference benchmarks
Benchmark	GPT-6.1 Sol	MiniMax-M2
LMArena Text	1447	1340
LMArena Creative Writing	1432	1286
LMArena Multi-Turn	1449	1361

Frequently asked questions

Is GPT-6.1 Sol better than MiniMax-M2?

Which is cheaper, GPT-6.1 Sol or MiniMax-M2?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GPT-6.1 Sol lists at $2 and $10.

Is GPT-6.1 Sol or MiniMax-M2 better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 39.3 in the Noometry coding category.

Which has the bigger context window?

GPT-6.1 Sol does, with 1.05M tokens against 205K.

How many benchmarks do GPT-6.1 Sol and MiniMax-M2 share?

14 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and MiniMax-M2 has 21.