Noometry

Model comparison

Llama 3.1-70B vs Mistral Small 3.2

Mistral Small 3.2 is the stronger model overall, scoring 30.8 to 29.4 on the Noometry Index.

Last verified . 4 shared benchmarks.

Llama 3.1-70B Meta

29.4

Rank #299 Confirmed

Mistral Small 3.2 Mistral AI

30.8

Rank #271 Confirmed

Summary

  • They share 4 benchmarks with published results for both. Llama 3.1-70B scores higher in 1 category and Mistral Small 3.2 in 3 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where Mistral Small 3.2 leads 24.9 to 12.7.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B 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 $0.40 / $0.40 for Llama 3.1-70B.
  • Mistral Small 3.2 accepts more context: 256K tokens versus 128K.

Side by side

Llama 3.1-70BMistral Small 3.2
ProviderMetaMistral AI
Noometry Index29.430.8
Released2024-07-232025-06-20
WeightsOpenOpen
Context window128K256K
Max output4K16K
Input $ / M tokens$0.40$0.0938
Output $ / M tokens$0.40$0.25
Results tracked356

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Category by category

Coding Not comparable

Llama 3.1-70B: 29.8 (#292), Mistral Small 3.2: —

BenchmarkLlama 3.1-70BMistral Small 3.2
WeirdML9%—
BigCodeBench Instruct46.1%—
LMArena Coding1260—
BigCodeBench Complete54.8%—

Agentic & Tool Use Not comparable

Llama 3.1-70B: 24.9 (#104), Mistral Small 3.2: —

BenchmarkLlama 3.1-70BMistral Small 3.2
TheAgentCompany6.9%—
BALROG27.9%—

Reasoning Llama 3.1-70B leads

Llama 3.1-70B: 20.8 (#215), Mistral Small 3.2: 17.5 (#282)

BenchmarkLlama 3.1-70BMistral Small 3.2
Epoch Capabilities Index125.91131.73
Kagi LLM Benchmark—40.4%
Chess Puzzles—1%
LMArena Hard Prompts1241—
DTBench60%—
LMCA14.8%—

Math Mistral Small 3.2 leads

Llama 3.1-70B: 12.7 (#298), Mistral Small 3.2: 24.9 (#251)

BenchmarkLlama 3.1-70BMistral Small 3.2
OTIS Mock AIME 2024-20253.6%30.3%
Omni-MATH21%—
LMArena Math1252—
MATH Level 536.7%—

Knowledge Mistral Small 3.2 leads

Llama 3.1-70B: 24.1 (#264), Mistral Small 3.2: 26.8 (#249)

BenchmarkLlama 3.1-70BMistral Small 3.2
GPQA Diamond44.2%49.1%
MMLU-Pro65.3%—
GPQA (HELM)42.6%—
LMArena Expert1209—
MMLU80.1%—

Multilingual Not comparable

Llama 3.1-70B: 38.9 (#220), Mistral Small 3.2: —

BenchmarkLlama 3.1-70BMistral Small 3.2
LMArena Non-English1219—
LMArena Chinese1215—
LMArena French1260—
LMArena German1222—
LMArena Japanese1132—
LMArena Korean1140—
LMArena Russian1234—
LMArena Spanish1253—

Instruction Following Not comparable

Llama 3.1-70B: 65.5 (#218), Mistral Small 3.2: —

BenchmarkLlama 3.1-70BMistral Small 3.2
IFEval82.1%—
LMArena Instruction Following1231—

Long Context Not comparable

Llama 3.1-70B: 37.6 (#208), Mistral Small 3.2: —

BenchmarkLlama 3.1-70BMistral Small 3.2
LMArena Longer Query1241—

Writing & Preference Mistral Small 3.2 leads

Llama 3.1-70B: 35.6 (#262), Mistral Small 3.2: 45.1 (#219)

BenchmarkLlama 3.1-70BMistral Small 3.2
EQ-Bench Creative Writing7841255
LMArena Text1261—
LMArena Creative Writing1232—
WildBench75.8%—
LMArena Multi-Turn1256—

Frequently asked questions

Is Llama 3.1-70B better than Mistral Small 3.2?

Mistral Small 3.2 is the stronger model overall, scoring 30.8 to 29.4 on the Noometry Index.

Which is cheaper, Llama 3.1-70B 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 3.1-70B lists at $0.40 and $0.40.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 128K.

How many benchmarks do Llama 3.1-70B and Mistral Small 3.2 share?

4 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Mistral Small 3.2 has 6.

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