Model comparison

Llama 3.2 1B vs Mistral Large 4

Mistral Large 4 is the stronger model overall, scoring 43.1 to 20.1 on the Noometry Index. Llama 3.2 1B costs 15× less per token, which makes it the better buy when Mistral Large 4's lead doesn't matter for your workload.

Last verified October 10, 2026. 12 shared benchmarks.

Llama 3.2 1B

Summary

They share 12 benchmarks with published results for both. Llama 3.2 1B scores higher in 0 categories and Mistral Large 4 in 8 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where Mistral Large 4 leads 60.4 to 21.3.
Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.68 / $2.09 for Mistral Large 4.
Mistral Large 4 accepts more context: 1.05M tokens versus 60K.
Llama 3.2 1B has downloadable open weights; the other is API-only.

Side by side

Llama 3.2 1B and Mistral Large 4 specifications
	Llama 3.2 1B	Mistral Large 4
Provider	Meta	Mistral AI
Noometry Index	20.1	43.1
Released	2024-09-24	2026-10-06
Weights	Open	Proprietary
Context window	60K	1.05M
Max output	54K	262K
Input $ / M tokens	$0.027	$0.68
Output $ / M tokens	$0.20	$2.09
Results tracked	22	15

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Category by category

Coding Mistral Large 4 leads

Llama 3.2 1B: 21.1 (#338), Mistral Large 4: 48.6 (#57)

Coding benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Coding	1070	1475
LMArena WebDev	—	1541
BigCodeBench Instruct	8.2%	—
BigCodeBench Complete	11.3%	—

Agentic & Tool Use Not comparable

Llama 3.2 1B: 14.6 (#150), Mistral Large 4: —

Agentic & Tool Use benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
Berkeley Function Calling Leaderboard	10.8%	—
BALROG	6.6%	—

Reasoning Mistral Large 4 leads

Llama 3.2 1B: 16.2 (#308), Mistral Large 4: 22.5 (#192)

Reasoning benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Hard Prompts	1044	1444
NYT Connections (extended)	—	27.4%
Chess Puzzles	0%	—
Epoch Capabilities Index	101.99	—

Math Mistral Large 4 leads

Llama 3.2 1B: 10.4 (#313), Mistral Large 4: 40.4 (#91)

Math benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Math	1086	1488
OTIS Mock AIME 2024-2025	0.6%	—

Knowledge Mistral Large 4 leads

Llama 3.2 1B: 7.2 (#312), Mistral Large 4: 36.6 (#166)

Knowledge benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Expert	1007	1447
GPQA Diamond	23.9%	—
SimpleQA Verified	—	20%

Multilingual Mistral Large 4 leads

Llama 3.2 1B: 23.8 (#292), Mistral Large 4: 52.6 (#82)

Multilingual benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Non-English	973	1415
LMArena Chinese	959	1491
LMArena Russian	941	1414
LMArena German	1014	—

Instruction Following Mistral Large 4 leads

Llama 3.2 1B: 52.4 (#290), Mistral Large 4: 75.0 (#76)

Instruction Following benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Instruction Following	1031	1424

Long Context Mistral Large 4 leads

Llama 3.2 1B: 31.9 (#274), Mistral Large 4: 43.6 (#89)

Long Context benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Longer Query	1050	1429

Writing & Preference Mistral Large 4 leads

Llama 3.2 1B: 21.3 (#310), Mistral Large 4: 60.4 (#97)

Writing & Preference benchmarks
Benchmark	Llama 3.2 1B	Mistral Large 4
LMArena Text	1055	1427
LMArena Creative Writing	1033	1361
LMArena Multi-Turn	1030	1424
EQ-Bench Creative Writing	200	—

Frequently asked questions

Is Llama 3.2 1B better than Mistral Large 4?

Which is cheaper, Llama 3.2 1B or Mistral Large 4?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Mistral Large 4 lists at $0.68 and $2.09.

Is Llama 3.2 1B or Mistral Large 4 better for coding?

Mistral Large 4 scores higher on coding benchmarks: 48.6 versus 21.1 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 4 does, with 1.05M tokens against 60K.

How many benchmarks do Llama 3.2 1B and Mistral Large 4 share?

12 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Mistral Large 4 has 15.