Noometry

Model comparison

Llama 3.2 3B vs Mixtral 8x22B

Llama 3.2 3B is the stronger model overall, scoring 28.9 to 27.1 on the Noometry Index.

Last verified . 15 shared benchmarks.

Llama 3.2 3B Meta

28.9

Rank #321 Confirmed

Mixtral 8x22B Mistral AI

27.1

Rank #333 Confirmed

Summary

  • They share 15 benchmarks with published results for both. Llama 3.2 3B scores higher in 4 categories and Mixtral 8x22B in 5 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Llama 3.2 3B leads 29.7 to 15.1.
  • The biggest single-benchmark swing is BigCodeBench Complete: 28.3% for Llama 3.2 3B and 50.2% for Mixtral 8x22B.
  • Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • Llama 3.2 3B accepts more context: 131K tokens versus 64K.

Side by side

Llama 3.2 3BMixtral 8x22B
ProviderMetaMistral AI
Noometry Index28.927.1
Released2024-09-242024-04-17
WeightsOpenOpen
Context window131K64K
Max output118K64K
Input $ / M tokens$0.05$2
Output $ / M tokens$0.33$6
Results tracked1834

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Category by category

Coding Llama 3.2 3B leads

Llama 3.2 3B: 27.6 (#319), Mixtral 8x22B: 24.2 (#329)

BenchmarkLlama 3.2 3BMixtral 8x22B
BigCodeBench Instruct23.4%40.6%
LMArena Coding10981166
BigCodeBench Complete28.3%50.2%
WeirdML—3.2%
HumanEval+—72%
MBPP+—64.3%

Agentic & Tool Use Mixtral 8x22B leads

Llama 3.2 3B: 20.1 (#143), Mixtral 8x22B: 23.1 (#127)

BenchmarkLlama 3.2 3BMixtral 8x22B
Berkeley Function Calling Leaderboard21.9%—
Cybench—7.5%
BALROG10.1%—

Reasoning Llama 3.2 3B leads

Llama 3.2 3B: 21.0 (#228), Mixtral 8x22B: 19.9 (#248)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Hard Prompts10951150
DTBench—55.1%
Epoch Capabilities Index—122.03
ForecastBench—56.3

Math Llama 3.2 3B leads

Llama 3.2 3B: 32.4 (#214), Mixtral 8x22B: 22.9 (#275)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Math11261184
Omni-MATH—16.3%
MATH Level 5—24.2%

Knowledge Llama 3.2 3B leads

Llama 3.2 3B: 29.7 (#235), Mixtral 8x22B: 15.1 (#293)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Expert10901113
GPQA Diamond—34.1%
MMLU-Pro—46%
GPQA (HELM)—33.4%
MMLU—77.8%

Multilingual Mixtral 8x22B leads

Llama 3.2 3B: 26.2 (#281), Mixtral 8x22B: 32.8 (#255)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Non-English10191128
LMArena Chinese10171116
LMArena German10561141
LMArena Russian9491158
LMArena French—1166
LMArena Japanese—1037
LMArena Korean—1057
LMArena Spanish—1151

Instruction Following Mixtral 8x22B leads

Llama 3.2 3B: 56.0 (#275), Mixtral 8x22B: 57.7 (#266)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Instruction Following10891147
IFEval—72.4%

Long Context Mixtral 8x22B leads

Llama 3.2 3B: 33.4 (#261), Mixtral 8x22B: 34.7 (#247)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Longer Query11001144

Writing & Preference Mixtral 8x22B leads

Llama 3.2 3B: 24.7 (#307), Mixtral 8x22B: 36.9 (#262)

BenchmarkLlama 3.2 3BMixtral 8x22B
LMArena Text11101162
LMArena Creative Writing10941141
LMArena Multi-Turn11051130
EQ-Bench Creative Writing595—
WildBench—71.1%

Frequently asked questions

Is Llama 3.2 3B better than Mixtral 8x22B?

Llama 3.2 3B is the stronger model overall, scoring 28.9 to 27.1 on the Noometry Index.

Which is cheaper, Llama 3.2 3B or Mixtral 8x22B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is Llama 3.2 3B or Mixtral 8x22B better for coding?

Llama 3.2 3B scores higher on coding benchmarks: 27.6 versus 24.2 in the Noometry coding category.

Which has the bigger context window?

Llama 3.2 3B does, with 131K tokens against 64K.

How many benchmarks do Llama 3.2 3B and Mixtral 8x22B share?

15 benchmarks have published results for both models. Llama 3.2 3B has 18 scored results on Noometry and Mixtral 8x22B has 34.

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