Model comparison

Llama 3.2 1B vs MiniMax M1

MiniMax M1 is the stronger model overall, scoring 39.7 to 19.9 on the Noometry Index. Llama 3.2 1B costs 12× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.

Last verified October 10, 2026. 13 shared benchmarks.

Llama 3.2 1B

Summary

They share 13 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and MiniMax M1 in 8 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where MiniMax M1 leads 53.3 to 21.4.
Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.40 / $2.20 for MiniMax M1.
MiniMax M1 accepts more context: 1M tokens versus 60K.

Side by side

Llama 3.2 1B and MiniMax M1 specifications
	Llama 3.2 1B	MiniMax M1
Provider	Meta	MiniMax
Noometry Index	19.9	39.7
Released	2024-09-24	2025-06-13
Weights	Open	Open
Context window	60K	1M
Max output	54K	40K
Input $ / M tokens	$0.027	$0.40
Output $ / M tokens	$0.20	$2.20
Results tracked	22	18

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Category by category

Coding MiniMax M1 leads

Llama 3.2 1B: 20.6 (#333), MiniMax M1: 39.2 (#149)

Coding benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Coding	1071	1359
BigCodeBench Instruct	8.2%	—
BigCodeBench Complete	11.3%	—

Agentic & Tool Use Not comparable

Llama 3.2 1B: 14.5 (#142), MiniMax M1: —

Agentic & Tool Use benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
Berkeley Function Calling Leaderboard	10.8%	—
BALROG	6.6%	—

Reasoning MiniMax M1 leads

Llama 3.2 1B: 15.6 (#304), MiniMax M1: 25.8 (#125)

Reasoning benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Hard Prompts	1044	1340
Chess Puzzles	0%	—
Epoch Capabilities Index	101.95	—

Math MiniMax M1 leads

Llama 3.2 1B: 9.7 (#308), MiniMax M1: 34.8 (#152)

Math benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Math	1086	1360
OTIS Mock AIME 2024-2025	0.6%	—

Knowledge MiniMax M1 leads

Llama 3.2 1B: 7.2 (#307), MiniMax M1: 35.7 (#168)

Knowledge benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Expert	1007	1316
GPQA Diamond	23.9%	—

Multilingual MiniMax M1 leads

Llama 3.2 1B: 23.9 (#287), MiniMax M1: 46.0 (#157)

Multilingual benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Non-English	973	1320
LMArena Chinese	958	1361
LMArena German	1014	1350
LMArena Russian	941	1330
LMArena French	—	1369
LMArena Japanese	—	1220
LMArena Korean	—	1263
LMArena Spanish	—	1354

Instruction Following MiniMax M1 leads

Llama 3.2 1B: 52.6 (#285), MiniMax M1: 69.5 (#169)

Instruction Following benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Instruction Following	1031	1312

Long Context MiniMax M1 leads

Llama 3.2 1B: 31.9 (#269), MiniMax M1: 41.4 (#136)

Long Context benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Longer Query	1050	1326
Fiction.LiveBench	—	69.4%

Writing & Preference MiniMax M1 leads

Llama 3.2 1B: 21.4 (#305), MiniMax M1: 53.3 (#155)

Writing & Preference benchmarks
Benchmark	Llama 3.2 1B	MiniMax M1
LMArena Text	1055	1343
LMArena Creative Writing	1033	1298
LMArena Multi-Turn	1030	1335
EQ-Bench Creative Writing	200	—

Frequently asked questions

Is Llama 3.2 1B better than MiniMax M1?

Which is cheaper, Llama 3.2 1B or MiniMax M1?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; MiniMax M1 lists at $0.40 and $2.20.

Is Llama 3.2 1B or MiniMax M1 better for coding?

MiniMax M1 scores higher on coding benchmarks: 39.2 versus 20.6 in the Noometry coding category.

Which has the bigger context window?

MiniMax M1 does, with 1M tokens against 60K.

How many benchmarks do Llama 3.2 1B and MiniMax M1 share?

13 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and MiniMax M1 has 18.