Model comparison

Llama 3-8B vs MiniMax-M2.5

MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 25.5 on the Noometry Index.

Last verified . 18 shared benchmarks.

Llama 3-8B Meta

25.5

Rank #344 Confirmed

MiniMax-M2.5 MiniMax

38.3

Rank #188 Confirmed

Summary

  • They share 18 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and MiniMax-M2.5 in 8 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where MiniMax-M2.5 leads 39.2 to 7.8.

Side by side

Llama 3-8B and MiniMax-M2.5 specifications
Llama 3-8BMiniMax-M2.5
ProviderMetaMiniMax
Noometry Index25.538.3
Released2024-04-182026-02-12
WeightsOpenOpen
Context window—205K
Max output—131K
Input $ / M tokens—$0.30
Output $ / M tokens—$1.20
Results tracked3433

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Category by category

Coding MiniMax-M2.5 leads

Llama 3-8B: 31.0 (#289), MiniMax-M2.5: 48.1 (#58)

Coding benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Coding11521381
SWE-bench Verified (bash only)—75.8%
LMArena WebDev—1387
SWE-bench Multilingual—68.3%
BigCodeBench Instruct31.9%—
BigCodeBench Complete36.9%—
ALE-Bench—618.17
HumanEval+56.7%—
MBPP+54.8%—

Agentic & Tool Use Not comparable

Llama 3-8B: —, MiniMax-M2.5: 30.4 (#77)

Agentic & Tool Use benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
Terminal-Bench—42.7%
Vending-Bench 2—-23.16

Reasoning MiniMax-M2.5 leads

Llama 3-8B: 14.3 (#326), MiniMax-M2.5: 17.5 (#292)

Reasoning benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Hard Prompts11331372
Epoch Capabilities Index116.45146.68
ARC-AGI-2—4.9%
Kagi LLM Benchmark—55.2%
NYT Connections (extended)—16.8%
ARC-AGI-1—63.7%
Chess Puzzles0%—
DTBench43.9%—
Adversarial NLI57.3%—
ForecastBench58.6—
WinoGrande75.7%—

Math MiniMax-M2.5 leads

Llama 3-8B: 8.8 (#323), MiniMax-M2.5: 26.9 (#253)

Math benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Math11511378
OTIS Mock AIME 2024-20251.9%—
ProofBench—4%
MATH Level 56.1%—

Knowledge MiniMax-M2.5 leads

Llama 3-8B: 7.8 (#308), MiniMax-M2.5: 39.2 (#135)

Knowledge benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Expert11131379
GPQA Diamond26.1%—
Vectara Hallucination Rate—9.1%
ARC (AI2) Challenge82.8%—
MMLU68.8%—
OpenBookQA82.6%—
TriviaQA67.7%—

Multilingual MiniMax-M2.5 leads

Llama 3-8B: 30.8 (#261), MiniMax-M2.5: 47.1 (#152)

Multilingual benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Non-English10981338
LMArena Chinese10761393
LMArena French11591362
LMArena German11041362
LMArena Japanese9671171
LMArena Korean10041232
LMArena Russian11091358
LMArena Spanish11731354

Instruction Following MiniMax-M2.5 leads

Llama 3-8B: 58.4 (#260), MiniMax-M2.5: 71.5 (#148)

Instruction Following benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Instruction Following11271353

Long Context MiniMax-M2.5 leads

Llama 3-8B: 34.2 (#251), MiniMax-M2.5: 37.5 (#216)

Long Context benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Longer Query11281366
CL-bench—11.4%
CL-bench Life—6.3%

Writing & Preference MiniMax-M2.5 leads

Llama 3-8B: 37.5 (#256), MiniMax-M2.5: 53.9 (#153)

Writing & Preference benchmarks
BenchmarkLlama 3-8BMiniMax-M2.5
LMArena Text11661359
LMArena Creative Writing11501331
LMArena Multi-Turn11521364
EQ-Bench Creative Writing—1361

Frequently asked questions

Is Llama 3-8B better than MiniMax-M2.5?

MiniMax-M2.5 is the stronger model overall, scoring 38.3 to 25.5 on the Noometry Index.

Is Llama 3-8B or MiniMax-M2.5 better for coding?

MiniMax-M2.5 scores higher on coding benchmarks: 48.1 versus 31.0 in the Noometry coding category.

How many benchmarks do Llama 3-8B and MiniMax-M2.5 share?

18 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and MiniMax-M2.5 has 33.

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