Noometry

Model comparison

GPT-4.1 nano vs Mistral Large 3

Mistral Large 3 is the stronger model overall, scoring 39.1 to 27.9 on the Noometry Index. GPT-4.1 nano costs 2.1× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.

Last verified . 17 shared benchmarks.

GPT-4.1 nano OpenAI

27.9

Rank #327 Confirmed

Mistral Large 3 Mistral AI

39.1

Rank #176 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GPT-4.1 nano scores higher in 0 categories and Mistral Large 3 in 9 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Mistral Large 3 leads 60.0 to 40.5.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 33.3% for GPT-4.1 nano and 50.9% for Mistral Large 3.
  • GPT-4.1 nano is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $0.75 for Mistral Large 3.
  • GPT-4.1 nano accepts more context: 1.05M tokens versus 262K.
  • Mistral Large 3 has downloadable open weights; the other is API-only.

Side by side

GPT-4.1 nanoMistral Large 3
ProviderOpenAIMistral AI
Noometry Index27.939.1
Released2025-04-142025-12-02
WeightsProprietaryOpen
Context window1.05M262K
Max output33K8K
Input $ / M tokens$0.10$0.25
Output $ / M tokens$0.40$0.75
Results tracked3824

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Mistral Large 3 leads

GPT-4.1 nano: 24.1 (#330), Mistral Large 3: 34.4 (#237)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Coding13061448
Aider Polyglot8.9%—
LMArena WebDev—1230
SciCode25.9%—
WeirdML19%—

Agentic & Tool Use Not comparable

GPT-4.1 nano: 26.5 (#104), Mistral Large 3: —

BenchmarkGPT-4.1 nanoMistral Large 3
Berkeley Function Calling Leaderboard33%—

Reasoning Mistral Large 3 leads

GPT-4.1 nano: 8.5 (#349), Mistral Large 3: 15.2 (#319)

BenchmarkGPT-4.1 nanoMistral Large 3
Kagi LLM Benchmark33.3%50.9%
LMArena Hard Prompts12861429
ARC-AGI-20%—
NYT Connections (extended)—7.5%
ARC-AGI-10%—
CritPt0%—
Thematic Generalization—23%
DTBench52.5%—
LMCA5.5%—
Epoch Capabilities Index129.62—

Math Mistral Large 3 leads

GPT-4.1 nano: 26.9 (#252), Mistral Large 3: 38.7 (#129)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Math12741414
OTIS Mock AIME 2024-202528.9%—
Omni-MATH36.7%—
MATH Level 570%—
FrontierMath (Feb 2025 set)1%—

Knowledge Mistral Large 3 leads

GPT-4.1 nano: 21.8 (#273), Mistral Large 3: 36.0 (#177)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Expert12721421
GPQA Diamond48.9%—
SimpleQA Verified6%—
MMLU-Pro55%—
Vectara Hallucination Rate—14.5%
GPQA (HELM)50.7%—

Multimodal Mistral Large 3 leads

GPT-4.1 nano: 29.2 (#113), Mistral Large 3: 38.2 (#66)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Vision10631221

Multilingual Mistral Large 3 leads

GPT-4.1 nano: 41.6 (#205), Mistral Large 3: 52.5 (#84)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Non-English12601413
LMArena Chinese12701447
LMArena German12881437
LMArena Japanese11981394
LMArena Russian12611411
LMArena French—1455
LMArena Korean—1384
LMArena Spanish—1440

Instruction Following Mistral Large 3 leads

GPT-4.1 nano: 67.8 (#193), Mistral Large 3: 74.0 (#108)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Instruction Following12671403
IFEval84.3%—

Long Context Mistral Large 3 leads

GPT-4.1 nano: 23.7 (#296), Mistral Large 3: 43.1 (#105)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Longer Query12831413
Fiction.LiveBench25%—

Writing & Preference Mistral Large 3 leads

GPT-4.1 nano: 40.5 (#243), Mistral Large 3: 60.0 (#101)

BenchmarkGPT-4.1 nanoMistral Large 3
LMArena Text12851428
LMArena Creative Writing12601386
EQ-Bench Creative Writing9461412
LMArena Multi-Turn12771429
WildBench81.2%—

Frequently asked questions

Is GPT-4.1 nano better than Mistral Large 3?

Mistral Large 3 is the stronger model overall, scoring 39.1 to 27.9 on the Noometry Index. GPT-4.1 nano costs 2.1× less per token, which makes it the better buy when Mistral Large 3's lead doesn't matter for your workload.

Which is cheaper, GPT-4.1 nano or Mistral Large 3?

GPT-4.1 nano is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Mistral Large 3 lists at $0.25 and $0.75.

Is GPT-4.1 nano or Mistral Large 3 better for coding?

Mistral Large 3 scores higher on coding benchmarks: 34.4 versus 24.1 in the Noometry coding category.

Which has the bigger context window?

GPT-4.1 nano does, with 1.05M tokens against 262K.

How many benchmarks do GPT-4.1 nano and Mistral Large 3 share?

17 benchmarks have published results for both models. GPT-4.1 nano has 38 scored results on Noometry and Mistral Large 3 has 24.

Related comparisons

Go deeper