Commonsense · Microsoft

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

Phi-3.5 Chat scores 80.9 on HellaSwag, placing it #373 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
80.9
0–100 scale
Rank
#373
of 600
Percentile
38th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
15.2
points

Score distribution

The chart shows the top 10 models on HellaSwag, with Phi-3.5 Chat 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 Chat sits at #373 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 15.2 points. The median model in this index scores 83.6, which puts Phi-3.5 Chat below the midpoint.

Microsoft models average 76.8 on this benchmark. Phi-3.5 Chat is 4.1 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 Chat is 0.7 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 80.9 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 $2.64 per million input tokens, Phi-3.5 Chat 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
OLMo 2 Chat Allen Institute for AI 16384 $2.94 70.6
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Mixtral Base Mistral AI 65536 $2.95 71.1
Mixtral Groq Chat Groq 8192 $3.09 72.0
Phi-3.5 Chat Microsoft 16384 $2.64 69.0
DBRX Chat Databricks 65536 $3.07 71.7
Gemini 2.5 Pro Nano Google DeepMind 32768 $7.28 69.2

Other benchmarks for Phi-3.5 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.4 345 43th
GPQA Diamond 64.9 362 40th
SWE-bench Verified 56.6 372 38th
HumanEval 71.0 389 35th
MATH-500 69.0 388 35th
AIME 2025 64.6 346 42th
LiveCodeBench 62.6 340 43th
IFEval 79.2 352 41th
TruthfulQA 72.4 377 37th
MMMU 63.7 393 35th
Arena Elo 1338.0 380 37th

FAQ

What score does Phi-3.5 Chat get on HellaSwag?

Phi-3.5 Chat scores 80.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Phi-3.5 Chat rank on HellaSwag?

It ranks #373 of 600 models, in the 38th percentile. The leader is GPT-5.2 Max at 96.1.

Is Phi-3.5 Chat 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 Chat cost?

Phi-3.5 Chat costs $2.64 per million input tokens and $12.13 per million output tokens.

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