Model comparison

GPT-3.5-turbo vs Phi-4 Mini

Phi-4 Mini is the stronger model overall, scoring 30.9 to 23.2 on the Noometry Index.

Last verified . 0 shared benchmarks.

GPT-3.5-turbo OpenAI

23.2

Rank #350 Confirmed

Phi-4 Mini Microsoft

30.9

Rank #283 Reported

Summary

  • The widest gap is in knowledge, where Phi-4 Mini leads 25.3 to 10.0.
  • Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.50 / $1.50 for GPT-3.5-turbo.
  • Phi-4 Mini accepts more context: 128K tokens versus 16K.
  • Phi-4 Mini has downloadable open weights; the other is API-only.

Side by side

GPT-3.5-turbo and Phi-4 Mini specifications
GPT-3.5-turboPhi-4 Mini
ProviderOpenAIMicrosoft
Noometry Index23.230.9
Released2023-03-012024-12-11
WeightsProprietaryOpen
Context window16K128K
Max output4K4K
Input $ / M tokens$0.50$0.075
Output $ / M tokens$1.50$0.30
Results tracked443

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Category by category

Coding Phi-4 Mini leads

GPT-3.5-turbo: 23.9 (#331), Phi-4 Mini: 28.1 (#317)

Coding benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
SciCode—10.8%
WeirdML3.5%—
BigCodeBench Instruct39.1%—
LMArena Coding1136—
BigCodeBench Complete50.6%—
HumanEval+70.7%—
MBPP+69.7%—

Agentic & Tool Use Not comparable

GPT-3.5-turbo: —, Phi-4 Mini: —

Agentic & Tool Use benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
METR Time Horizons21.5%—

Reasoning Phi-4 Mini leads

GPT-3.5-turbo: 13.8 (#332), Phi-4 Mini: 22.4 (#195)

Reasoning benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
CritPt—0%
Chess Puzzles0%—
LMArena Hard Prompts1108—
Mystery Game Puzzles3%—
DTBench48.5%—
LMCA9.7%—
Adversarial NLI58.1%—
BIG-Bench Hard61.6%—
CommonsenseQA 2.057%—
Epoch Capabilities Index118.55—
ForecastBench50.4—
WinoGrande81.6%—

Math Not comparable

GPT-3.5-turbo: 6.3 (#327), Phi-4 Mini: —

Math benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
FrontierMath (Tiers 1-3)0%—
OTIS Mock AIME 2024-20252.2%—
LMArena Math1142—
MATH Level 515.9%—
GSM8K57.8%—

Knowledge Phi-4 Mini leads

GPT-3.5-turbo: 10.0 (#303), Phi-4 Mini: 25.3 (#262)

Knowledge benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
GPQA Diamond28%—
Vectara Hallucination Rate—23.5%
LMArena Expert1070—
ARC (AI2) Challenge87.4%—
BoolQ87%—
MMLU71.4%—
OpenBookQA86%—
TriviaQA85.8%—

Multilingual Not comparable

GPT-3.5-turbo: 31.5 (#258), Phi-4 Mini: —

Multilingual benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
LMArena Non-English1108—
LMArena Chinese1075—
LMArena French1118—
LMArena German1090—
LMArena Japanese1043—
LMArena Korean1019—
LMArena Russian1123—
LMArena Spanish1121—

Instruction Following Not comparable

GPT-3.5-turbo: 57.9 (#262), Phi-4 Mini: —

Instruction Following benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
LMArena Instruction Following1119—

Long Context Not comparable

GPT-3.5-turbo: 34.0 (#254), Phi-4 Mini: —

Long Context benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
LMArena Longer Query1121—

Writing & Preference Not comparable

GPT-3.5-turbo: 25.3 (#305), Phi-4 Mini: —

Writing & Preference benchmarks
BenchmarkGPT-3.5-turboPhi-4 Mini
LMArena Text1125—
LMArena Creative Writing1092—
EQ-Bench Creative Writing451—
LMArena Multi-Turn1117—

Frequently asked questions

Is GPT-3.5-turbo better than Phi-4 Mini?

Phi-4 Mini is the stronger model overall, scoring 30.9 to 23.2 on the Noometry Index.

Which is cheaper, GPT-3.5-turbo or Phi-4 Mini?

Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 per million output tokens; GPT-3.5-turbo lists at $0.50 and $1.50.

Is GPT-3.5-turbo or Phi-4 Mini better for coding?

Phi-4 Mini scores higher on coding benchmarks: 28.1 versus 23.9 in the Noometry coding category.

Which has the bigger context window?

Phi-4 Mini does, with 128K tokens against 16K.

How many benchmarks do GPT-3.5-turbo and Phi-4 Mini share?

0 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and Phi-4 Mini has 3.

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