Noometry

Model comparison

GPT-4.1 nano vs Mixtral 8x7B

GPT-4.1 nano and Mixtral 8x7B score almost the same on the Noometry Index (27.9 vs 27.1), so choose on price, context window or the category you care about most.

Last verified . 23 shared benchmarks.

GPT-4.1 nano OpenAI

27.9

Rank #327 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 23 benchmarks with published results for both. GPT-4.1 nano scores higher in 5 categories and Mixtral 8x7B in 3 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in instruction following, where GPT-4.1 nano leads 67.8 to 51.0.
  • The biggest single-benchmark swing is MATH Level 5: 70% for GPT-4.1 nano and 10% for Mixtral 8x7B.
  • GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
  • GPT-4.1 nano 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 nanoMixtral 8x7B
ProviderOpenAIMistral AI
Noometry Index27.927.1
Released2025-04-142023-12-11
WeightsProprietaryOpen
Context window1.05M32K
Max output33K32K
Input $ / M tokens$0.10$0.70
Output $ / M tokens$0.40$0.70
Results tracked3838

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Category by category

Coding Mixtral 8x7B leads

GPT-4.1 nano: 24.1 (#330), Mixtral 8x7B: 32.8 (#269)

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Coding13061126
Aider Polyglot8.9%—
SciCode25.9%—
WeirdML19%—
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GPT-4.1 nano: 26.5 (#104), Mixtral 8x7B: —

BenchmarkGPT-4.1 nanoMixtral 8x7B
Berkeley Function Calling Leaderboard33%—

Reasoning Mixtral 8x7B leads

GPT-4.1 nano: 8.5 (#349), Mixtral 8x7B: 18.2 (#285)

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Hard Prompts12861115
DTBench52.5%49.6%
Epoch Capabilities Index129.62118.47
ARC-AGI-20%—
Kagi LLM Benchmark33.3%—
ARC-AGI-10%—
CritPt0%—
LMCA5.5%—
Adversarial NLI—55.2%
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GPT-4.1 nano leads

GPT-4.1 nano: 26.9 (#252), Mixtral 8x7B: 18.8 (#289)

BenchmarkGPT-4.1 nanoMixtral 8x7B
Omni-MATH36.7%10.5%
LMArena Math12741147
MATH Level 570%10%
OTIS Mock AIME 2024-202528.9%—
FrontierMath (Feb 2025 set)1%—
GSM8K—74.4%

Knowledge GPT-4.1 nano leads

GPT-4.1 nano: 21.8 (#273), Mixtral 8x7B: 11.0 (#301)

BenchmarkGPT-4.1 nanoMixtral 8x7B
GPQA Diamond48.9%30.6%
MMLU-Pro55%33.5%
GPQA (HELM)50.7%29.6%
LMArena Expert12721088
SimpleQA Verified6%—
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multimodal Not comparable

GPT-4.1 nano: 29.2 (#113), Mixtral 8x7B: —

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Vision1063—

Multilingual GPT-4.1 nano leads

GPT-4.1 nano: 41.6 (#205), Mixtral 8x7B: 29.6 (#266)

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Non-English12601077
LMArena Chinese12701055
LMArena German12881114
LMArena Japanese1198931
LMArena Russian12611090
LMArena French—1166
LMArena Korean—968
LMArena Spanish—1111

Instruction Following GPT-4.1 nano leads

GPT-4.1 nano: 67.8 (#193), Mixtral 8x7B: 51.0 (#297)

BenchmarkGPT-4.1 nanoMixtral 8x7B
IFEval84.3%57.5%
LMArena Instruction Following12671109

Long Context Mixtral 8x7B leads

GPT-4.1 nano: 23.7 (#296), Mixtral 8x7B: 33.4 (#260)

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Longer Query12831103
Fiction.LiveBench25%—

Writing & Preference GPT-4.1 nano leads

GPT-4.1 nano: 40.5 (#243), Mixtral 8x7B: 34.2 (#270)

BenchmarkGPT-4.1 nanoMixtral 8x7B
LMArena Text12851132
LMArena Creative Writing12601109
WildBench81.2%67.3%
LMArena Multi-Turn12771115
EQ-Bench Creative Writing946—

Frequently asked questions

Is GPT-4.1 nano better than Mixtral 8x7B?

GPT-4.1 nano and Mixtral 8x7B score almost the same on the Noometry Index (27.9 vs 27.1), so choose on price, context window or the category you care about most.

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

GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

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

Mixtral 8x7B scores higher on coding benchmarks: 32.8 versus 24.1 in the Noometry coding category.

Which has the bigger context window?

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

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

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

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