Safety · Microsoft

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

Phi-3.5 Base scores 73.0 on TruthfulQA, placing it #370 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
73.0
0–100 scale
Rank
#370
of 600
Percentile
38th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
18.1
points

Score distribution

The chart shows the top 10 models on TruthfulQA, with Phi-3.5 Base 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 Base sits at #370 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 18.1 points. The median model in this index scores 76.3, which puts Phi-3.5 Base below the midpoint.

Microsoft models average 67.5 on this benchmark. Phi-3.5 Base is 5.5 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 Base 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 73.0 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 $2.24 per million input tokens, Phi-3.5 Base 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
Fusion Pro OpenRouter 65536 $8.69 72.2
Sonar Pro Mini Perplexity 8192 $8.02 70.3
Claude 3.7 Sonnet Nano Anthropic 65536 $6.93 68.9
Nemotron Nano Instruct NVIDIA 32768 $2.33 67.4
Phi-3.5 Base Microsoft 65536 $2.24 66.6
Firesearch Pro Fireworks AI 32768 $7.67 70.4
Mixtral Base Mistral AI 65536 $2.95 71.1

Other benchmarks for Phi-3.5 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.4 379 37th
GPQA Diamond 60.3 402 33th
SWE-bench Verified 51.6 409 32th
HumanEval 73.1 371 38th
MATH-500 71.6 373 38th
AIME 2025 59.7 389 35th
LiveCodeBench 55.2 401 33th
IFEval 74.2 404 33th
HellaSwag 79.5 389 35th
MMMU 61.7 412 31th
Arena Elo 1315.0 400 33th

FAQ

What score does Phi-3.5 Base get on TruthfulQA?

Phi-3.5 Base scores 73.0 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does Phi-3.5 Base rank on TruthfulQA?

It ranks #370 of 600 models, in the 38th percentile. The leader is GPT-5.1 Max at 91.1.

Is Phi-3.5 Base 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 Base cost?

Phi-3.5 Base costs $2.24 per million input tokens and $10.25 per million output tokens.

Related