Model comparison

Llama 3-8B vs Mistral Small 3.2

Mistral Small 3.2 is the stronger model overall, scoring 30.8 to 25.3 on the Noometry Index.

Last verified October 10, 2026. 4 shared benchmarks.

Summary

They share 4 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Mistral Small 3.2 in 4 categories; 4 gaps are clear of the uncertainty.
The widest gap is in knowledge, where Mistral Small 3.2 leads 26.8 to 7.8.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.9% for Llama 3-8B and 30.3% for Mistral Small 3.2.
Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.14 / $0.14 for Llama 3-8B.
Mistral Small 3.2 accepts more context: 256K tokens versus 8K.

Side by side

Llama 3-8B and Mistral Small 3.2 specifications
	Llama 3-8B	Mistral Small 3.2
Provider	Meta	Mistral AI
Noometry Index	25.3	30.8
Released	2024-04-18	2025-06-20
Weights	Open	Open
Context window	8K	256K
Max output	8K	16K
Input $ / M tokens	$0.14	$0.0938
Output $ / M tokens	$0.14	$0.25
Results tracked	34	6

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Category by category

Coding Not comparable

Llama 3-8B: 30.5 (#285), Mistral Small 3.2: —

Coding benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
BigCodeBench Instruct	31.9%	—
LMArena Coding	1152	—
BigCodeBench Complete	36.9%	—
HumanEval+	56.7%	—
MBPP+	54.8%	—

Reasoning Mistral Small 3.2 leads

Llama 3-8B: 13.8 (#321), Mistral Small 3.2: 17.5 (#282)

Reasoning benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
Chess Puzzles	0%	1%
Epoch Capabilities Index	116.33	131.73
Kagi LLM Benchmark	—	40.4%
LMArena Hard Prompts	1133	—
DTBench	43.9%	—
Adversarial NLI	57.3%	—
ForecastBench	58.6	—
WinoGrande	75.7%	—

Math Mistral Small 3.2 leads

Llama 3-8B: 8.3 (#317), Mistral Small 3.2: 24.9 (#251)

Math benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
OTIS Mock AIME 2024-2025	1.9%	30.3%
LMArena Math	1151	—
MATH Level 5	6.1%	—

Knowledge Mistral Small 3.2 leads

Llama 3-8B: 7.8 (#303), Mistral Small 3.2: 26.8 (#249)

Knowledge benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
GPQA Diamond	26.1%	49.1%
LMArena Expert	1113	—
ARC (AI2) Challenge	82.8%	—
MMLU	68.8%	—
OpenBookQA	82.6%	—
TriviaQA	67.7%	—

Multilingual Not comparable

Llama 3-8B: 31.0 (#256), Mistral Small 3.2: —

Multilingual benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
LMArena Non-English	1098	—
LMArena Chinese	1076	—
LMArena French	1158	—
LMArena German	1104	—
LMArena Japanese	967	—
LMArena Korean	1003	—
LMArena Russian	1109	—
LMArena Spanish	1172	—

Instruction Following Not comparable

Llama 3-8B: 58.7 (#255), Mistral Small 3.2: —

Instruction Following benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
LMArena Instruction Following	1127	—

Long Context Not comparable

Llama 3-8B: 34.2 (#246), Mistral Small 3.2: —

Long Context benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
LMArena Longer Query	1128	—

Writing & Preference Mistral Small 3.2 leads

Llama 3-8B: 37.7 (#251), Mistral Small 3.2: 45.1 (#219)

Writing & Preference benchmarks
Benchmark	Llama 3-8B	Mistral Small 3.2
LMArena Text	1166	—
LMArena Creative Writing	1150	—
EQ-Bench Creative Writing	—	1255
LMArena Multi-Turn	1152	—

Frequently asked questions

Is Llama 3-8B better than Mistral Small 3.2?

Mistral Small 3.2 is the stronger model overall, scoring 30.8 to 25.3 on the Noometry Index.

Which is cheaper, Llama 3-8B or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Llama 3-8B lists at $0.14 and $0.14.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 8K.

How many benchmarks do Llama 3-8B and Mistral Small 3.2 share?

4 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Mistral Small 3.2 has 6.