Phi-4

Phi-4 is a non-reasoning model from Microsoft. 12 benchmarks count toward its score, in 5 categories.

availableShows if the model has enough results for an index.
IndexOverall score out of 100.23.3 ±8.2
CoverageShare of the index weight with results.65%
SpeedOutput tokens per second.12/s
Input / 1MUS dollars per 1M input tokens.$0.07
Output / 1MUS dollars per 1M output tokens.$0.14
ContextMaximum tokens in one request.16K
EloLMArena rating and rank.1217 (#300)

The index is a score out of 100. The ± range shows how much it can change.

24,126 votes. Elo shows what people prefer. It does not change the score.

CapabilitiesScore per category, out of 100.

Out of 100
AgenticMulti-step tasks with tools.
5.0
CodingCode writing and repair.
N/A
ReasoningLogic problems and puzzles.
23.8
MultimodalTasks with images and text.
N/A
KnowledgeFacts and expert knowledge.
29.5
MultilingualTasks in many languages.
N/A
InstructionTasks with strict rules in the prompt.
13.0
MathMath problems.
25.0

Results

12 counted
BenchmarkThe test name.CategoryThe capability that the test measures.ResultThe score from the publisher.IndexThis result as a score out of 100.RunThe settings of the run.DateDate of the result.Published byThe source of the result.
MATH level 5Math64.9%30.6Epoch AI
Artificial Analysis GPQA DiamondKnowledge57.5%27.5Artificial Analysis
GPQA diamondKnowledge56.1%30.0Epoch AI
Artificial Analysis IFBenchInstruction23.5%13.0Artificial Analysis
Artificial Analysis Omniscience AccuracyKnowledge14.1%31.3Artificial Analysis
OTIS Mock AIME 2024-2025Math13.8%19.3Epoch AI
Artificial Analysis Intelligence IndexKnowledge5.9%29.8Artificial Analysis
Artificial Analysis Humanity's Last ExamKnowledge3.8%28.7Artificial Analysis
Chess PuzzlesReasoning1.0%24.8Epoch AI
τ²-Bench Tool-Agent-User EvaluationAgentic0.0%5.0Victor Barres et al.
Artificial Analysis Long Context ReasoningReasoning0.0%8.3Artificial Analysis
Critical Physics TasksReasoning0.0%38.4Artificial Analysis

12 benchmarks count, from 12 of 12 results. A grey row does not count. Too few models took that benchmark.

Sources

BenchLM benchmark aggregationUsed with attribution; per-benchmark results credited to their original authorsOpenRouter, collected directlyNo licence statedEpoch AI, collected directlyCC BY — free to use and redistribute with attribution

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