Safety · Microsoft

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

Phi-3.5 Instruct scores 75.3 on TruthfulQA, placing it #326 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
75.3
0–100 scale
Rank
#326
of 600
Percentile
46th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
15.8
points

Score distribution

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

GPT-5.1 Max 91.1
Gemini 3 Pro Reasoning 90.3
GPT-5.1 Reasoning 90.0
GPT-5.2 Pro 90.0
GPT-5.2 89.7
Gemini 3 Pro Max 89.6
Grok 4 Reasoning 89.4
Qwen3-Max Max 89.3
GPT-5.1 89.2
GPT-5.1 Turbo 89.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
2 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
3 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
4 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
7 Grok 4 Reasoning xAI 2000000 $19.67 87.8
8 Qwen3-Max Max Alibaba Cloud 400000 $18.53 85.9
9 GPT-5.1 OpenAI 2000000 $19.01 86.0
10 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1

What this score means

On TruthfulQA, Phi-3.5 Instruct sits at #326 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 15.8 points. The median model in this index scores 76.3, which puts Phi-3.5 Instruct below the midpoint.

Microsoft models average 67.5 on this benchmark. Phi-3.5 Instruct is 7.8 points above that provider line, so it is a stronger result than the average Microsoft model.

Among open-weight models, the average is 72.3. Phi-3.5 Instruct is 3.0 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 75.3 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 $2.67 per million input tokens, Phi-3.5 Instruct is below the median input price of $4.00 across the 600 models scored on TruthfulQA. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Nemotron 4 Base NVIDIA 8192 $3.29 73.0
o3 Nano OpenAI 32768 $7.78 70.6
GPT-4.1 Nano OpenAI 32768 $7.42 70.5
Phi-3.5 Instruct Microsoft 16384 $2.67 70.1
o4 Nano OpenAI 65536 $8.61 72.0
Firesearch Fireworks AI 32768 $7.03 68.5

Other benchmarks for Phi-3.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.9 338 44th
GPQA Diamond 65.5 352 41th
SWE-bench Verified 56.1 376 37th
HumanEval 72.1 378 37th
MATH-500 74.6 338 44th
AIME 2025 66.6 323 46th
LiveCodeBench 59.6 373 38th
IFEval 79.2 353 41th
HellaSwag 82.2 343 43th
MMMU 65.3 379 37th
Arena Elo 1346.8 369 39th

FAQ

What score does Phi-3.5 Instruct get on TruthfulQA?

Phi-3.5 Instruct scores 75.3 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Phi-3.5 Instruct rank on TruthfulQA?

It ranks #326 of 600 models, in the 46th percentile. The leader is GPT-5.1 Max at 91.1.

Is Phi-3.5 Instruct good at TruthfulQA?

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 TruthfulQA score calculated?

TruthfulQA is a safety 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 Instruct cost?

Phi-3.5 Instruct costs $2.67 per million input tokens and $14.62 per million output tokens.

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