Commonsense · Microsoft

Phi-3.5 on HellaSwag: score, rank and what it means

Phi-3.5 scores 82.9 on HellaSwag, placing it #323 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
82.9
0–100 scale
Rank
#323
of 600
Percentile
46th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
13.2
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Phi-3.5 highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Phi-3.5 sits at #323 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 13.2 points. The median model in this index scores 83.6, which puts Phi-3.5 below the midpoint.

Microsoft models average 76.8 on this benchmark. Phi-3.5 is 6.1 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 80.2. Phi-3.5 is 2.7 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 82.9 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $2.81 per million input tokens, Phi-3.5 is below the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Sonnet 4.5 Nano Anthropic 8192 $8.93 72.0
Llama 3.3 Base Meta AI 32768 $3.63 74.0
Reka Flash Reka AI 128000 $9.95 74.1
Yi-Large Base 01.AI 16384 $2.78 70.3
Phi-3.5 Microsoft 16384 $2.81 70.9
Yi-Large Chat 01.AI 65536 $3.49 73.5
ERNIE 4.0 Mini Baidu 32768 $7.11 68.8

Other benchmarks for Phi-3.5

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 304 49th
GPQA Diamond 67.0 331 45th
SWE-bench Verified 60.9 308 49th
HumanEval 76.2 327 46th
MATH-500 75.4 316 47th
AIME 2025 60.6 383 36th
LiveCodeBench 59.8 371 38th
IFEval 77.1 377 37th
TruthfulQA 74.8 336 44th
MMMU 68.8 328 45th
Arena Elo 1356.7 350 42th

FAQ

What score does Phi-3.5 get on HellaSwag?

Phi-3.5 scores 82.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Phi-3.5 rank on HellaSwag?

It ranks #323 of 600 models, in the 46th percentile. The leader is GPT-5.2 Max at 96.1.

Is Phi-3.5 good at HellaSwag?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the HellaSwag score calculated?

HellaSwag is a commonsense benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Phi-3.5 cost?

Phi-3.5 costs $2.81 per million input tokens and $14.99 per million output tokens.

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