Model comparison

DeepSeek-R1 vs MiniMax-M2.1

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 38.4 on the Noometry Index. MiniMax-M2.1 costs 1.7× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.

Last verified October 10, 2026. 19 shared benchmarks.

DeepSeek-R1

DeepSeek

42.0

Rank #110 Confirmed

MiniMax-M2.1

MiniMax

38.4

Rank #177 Confirmed

Summary

They share 19 benchmarks with published results for both. DeepSeek-R1 scores higher in 8 categories and MiniMax-M2.1 in 1 category; 9 gaps are clear of the uncertainty.
The widest gap is in knowledge, where DeepSeek-R1 leads 44.3 to 37.7.
MiniMax-M2.1 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.50 / $2.15 for DeepSeek-R1.
MiniMax-M2.1 accepts more context: 205K tokens versus 164K.
MiniMax-M2.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-R1 and MiniMax-M2.1 specifications
	DeepSeek-R1	MiniMax-M2.1
Provider	DeepSeek	MiniMax
Noometry Index	42.0	38.4
Released	2025-01-20	2025-12-23
Weights	Proprietary	Open
Context window	164K	205K
Max output	64K	131K
Input $ / M tokens	$0.50	$0.30
Output $ / M tokens	$2.15	$1.20
Results tracked	52	22

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Category by category

Coding DeepSeek-R1 leads

DeepSeek-R1: 45.9 (#63), MiniMax-M2.1: 40.1 (#132)

Coding benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Coding	1427	1421
ALE-Bench	804.12	623.83
Aider Polyglot	71.4%	—
LMArena WebDev	—	1384
SciCode	35.7%	—
WeirdML	41.6%	—
LiveBench Coding	66.7%	—
AlgoTune	1.7	—

Agentic & Tool Use DeepSeek-R1 leads

DeepSeek-R1: 30.4 (#68), MiniMax-M2.1: 27.7 (#91)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
Terminal-Bench	—	36.6%
DeepResearch Bench	35.1%	—
BALROG	34.9%	—
METR Time Horizons	53.8%	—

Reasoning DeepSeek-R1 leads

DeepSeek-R1: 18.7 (#253), MiniMax-M2.1: 15.8 (#301)

Reasoning benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Hard Prompts	1415	1410
ARC-AGI-2	1.3%	—
SimpleBench	40.8%	—
Kagi LLM Benchmark	69.4%	—
NYT Connections (extended)	—	11.2%
ARC-AGI-1	21.2%	—
CritPt	1.1%	—
LiveBench Reasoning	83.2%	—
LiveBench Data Analysis	69.8%	—
Epoch Capabilities Index	141.3	—
ForecastBench	60	—
LiveBench	71.6%	—

Math DeepSeek-R1 leads

DeepSeek-R1: 42.0 (#70), MiniMax-M2.1: 35.6 (#142)

Math benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Math	1401	1396
OTIS Mock AIME 2024-2025	66.4%	—
Omni-MATH	42.4%	—
LiveBench Math	80.7%	—
MATH Level 5	96.6%	—

Knowledge DeepSeek-R1 leads

DeepSeek-R1: 44.3 (#81), MiniMax-M2.1: 37.7 (#143)

Knowledge benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
Vectara Hallucination Rate	11.3%	11.8%
LMArena Expert	1394	1432
GPQA Diamond	76.3%	—
MMLU-Pro	79.3%	—
Confabulations	12.7%	—
GPQA (HELM)	66.6%	—

Multilingual DeepSeek-R1 leads

DeepSeek-R1: 52.6 (#80), MiniMax-M2.1: 50.2 (#123)

Multilingual benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Non-English	1412	1378
LMArena Chinese	1443	1430
LMArena French	1415	1405
LMArena German	1405	1380
LMArena Japanese	1394	1287
LMArena Korean	1359	1297
LMArena Russian	1423	1386
LMArena Spanish	1410	1396

Instruction Following MiniMax-M2.1 leads

DeepSeek-R1: 72.2 (#138), MiniMax-M2.1: 74.0 (#108)

Instruction Following benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Instruction Following	1382	1399
LiveBench Instruction Following	80.5%	—
IFEval	78.4%	—

Long Context DeepSeek-R1 leads

DeepSeek-R1: 45.4 (#36), MiniMax-M2.1: 43.2 (#98)

Long Context benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Longer Query	1391	1416
Fiction.LiveBench	75%	—

Writing & Preference DeepSeek-R1 leads

DeepSeek-R1: 61.5 (#84), MiniMax-M2.1: 58.5 (#114)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1	MiniMax-M2.1
LMArena Text	1428	1392
LMArena Creative Writing	1406	1362
LMArena Multi-Turn	1404	1396
Short-Story Creative Writing	83%	—
EQ-Bench Creative Writing	1500	—
WildBench	82.8%	—
LiveBench Language	48.5%	—

Frequently asked questions

Is DeepSeek-R1 better than MiniMax-M2.1?

Which is cheaper, DeepSeek-R1 or MiniMax-M2.1?

MiniMax-M2.1 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; DeepSeek-R1 lists at $0.50 and $2.15.

Is DeepSeek-R1 or MiniMax-M2.1 better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 40.1 in the Noometry coding category.

Which has the bigger context window?

MiniMax-M2.1 does, with 205K tokens against 164K.

How many benchmarks do DeepSeek-R1 and MiniMax-M2.1 share?

19 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and MiniMax-M2.1 has 22.