Noometry

Model comparison

GPT-4.1 mini vs Mixtral 8x7B

GPT-4.1 mini is the stronger model overall, scoring 33.6 to 27.1 on the Noometry Index.

Last verified . 26 shared benchmarks.

GPT-4.1 mini OpenAI

33.6

Rank #240 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 26 benchmarks with published results for both. GPT-4.1 mini scores higher in 5 categories and Mixtral 8x7B in 3 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GPT-4.1 mini leads 34.7 to 11.0.
  • The biggest single-benchmark swing is MATH Level 5: 87.3% for GPT-4.1 mini and 10% for Mixtral 8x7B.
  • Both cost about the same: $0.40 input and $1.60 output per million tokens.
  • GPT-4.1 mini accepts more context: 1.05M tokens versus 32K.
  • Mixtral 8x7B has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 miniMixtral 8x7B
ProviderOpenAIMistral AI
Noometry Index33.627.1
Released2025-04-142023-12-11
WeightsProprietaryOpen
Context window1.05M32K
Max output33K32K
Input $ / M tokens$0.40$0.70
Output $ / M tokens$1.60$0.70
Results tracked4738

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Category by category

Coding Mixtral 8x7B leads

GPT-4.1 mini: 30.6 (#293), Mixtral 8x7B: 32.8 (#269)

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Coding13671126
SWE-bench Verified (bash only)23.9%—
Aider Polyglot32.4%—
SciCode40.4%—
WeirdML37.6%—
BigCodeBench Instruct48.9%—
CadEval16%—
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GPT-4.1 mini: 33.3 (#55), Mixtral 8x7B: —

BenchmarkGPT-4.1 miniMixtral 8x7B
Berkeley Function Calling Leaderboard50.5%—

Reasoning Mixtral 8x7B leads

GPT-4.1 mini: 10.8 (#340), Mixtral 8x7B: 18.2 (#285)

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Hard Prompts13491115
DTBench68.8%49.6%
Epoch Capabilities Index135.01118.47
ARC-AGI-20%—
Kagi LLM Benchmark48.6%—
ARC-AGI-13.5%—
CritPt0%—
Chess Puzzles7%—
Mystery Game Puzzles7%—
LMCA21.1%—
Adversarial NLI—55.2%
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GPT-4.1 mini leads

GPT-4.1 mini: 24.1 (#270), Mixtral 8x7B: 18.8 (#289)

BenchmarkGPT-4.1 miniMixtral 8x7B
Omni-MATH49.1%10.5%
LMArena Math13431147
MATH Level 587.3%10%
FrontierMath (Tiers 1-3)6.7%—
OTIS Mock AIME 2024-202544.7%—
FrontierMath (Feb 2025 set)4.5%—
GSM8K—74.4%

Knowledge GPT-4.1 mini leads

GPT-4.1 mini: 34.7 (#194), Mixtral 8x7B: 11.0 (#301)

BenchmarkGPT-4.1 miniMixtral 8x7B
GPQA Diamond65.8%30.6%
MMLU-Pro78.3%33.5%
GPQA (HELM)61.4%29.6%
LMArena Expert13381088
SimpleQA Verified12.7%—
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multimodal Not comparable

GPT-4.1 mini: 35.8 (#82), Mixtral 8x7B: —

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Vision1181—

Multilingual GPT-4.1 mini leads

GPT-4.1 mini: 45.7 (#166), Mixtral 8x7B: 29.6 (#266)

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Non-English13181077
LMArena Chinese13291055
LMArena French13581166
LMArena German13511114
LMArena Japanese1290931
LMArena Korean1298968
LMArena Russian13241090
LMArena Spanish13191111

Instruction Following GPT-4.1 mini leads

GPT-4.1 mini: 73.7 (#118), Mixtral 8x7B: 51.0 (#297)

BenchmarkGPT-4.1 miniMixtral 8x7B
IFEval90.4%57.5%
LMArena Instruction Following13331109

Long Context Mixtral 8x7B leads

GPT-4.1 mini: 31.8 (#275), Mixtral 8x7B: 33.4 (#260)

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Longer Query13441103
Fiction.LiveBench44.4%—

Writing & Preference GPT-4.1 mini leads

GPT-4.1 mini: 48.6 (#199), Mixtral 8x7B: 34.2 (#270)

BenchmarkGPT-4.1 miniMixtral 8x7B
LMArena Text13401132
LMArena Creative Writing13001109
WildBench83.8%67.3%
LMArena Multi-Turn13541115
EQ-Bench Creative Writing1147—

Frequently asked questions

Is GPT-4.1 mini better than Mixtral 8x7B?

GPT-4.1 mini is the stronger model overall, scoring 33.6 to 27.1 on the Noometry Index.

Which is cheaper, GPT-4.1 mini or Mixtral 8x7B?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.

Is GPT-4.1 mini or Mixtral 8x7B better for coding?

Mixtral 8x7B scores higher on coding benchmarks: 32.8 versus 30.6 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 mini does, with 1.05M tokens against 32K.

How many benchmarks do GPT-4.1 mini and Mixtral 8x7B share?

26 benchmarks have published results for both models. GPT-4.1 mini has 47 scored results on Noometry and Mixtral 8x7B has 38.

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