Commonsense · Databricks

DBRX 1.5B on HellaSwag: score, rank and what it means

DBRX 1.5B scores 66.2 on HellaSwag, placing it #575 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
66.2
0–100 scale
Rank
#575
of 600
Percentile
4th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
29.9
points

Score distribution

The chart shows the top 10 models on HellaSwag, with DBRX 1.5B 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, DBRX 1.5B sits at #575 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 29.9 points. The median model in this index scores 83.6, which puts DBRX 1.5B below the midpoint.

Databricks models average 76.4 on this benchmark. DBRX 1.5B is 10.2 points below that provider line, so it is a weaker result than the average Databricks model.

Among small open-weight models, the average is 70.2. DBRX 1.5B is 4.0 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 66.2 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 $0.32 per million input tokens, DBRX 1.5B 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
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Llama 3.3 Groq 1.5B Groq 4096 $0.46 50.0
Llama 3 DeepInfra 1.5B DeepInfra 32768 $0.48 48.8
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
DBRX 1.5B Databricks 16384 $0.32 47.0
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Llama 3 Lambda 1.5B Lambda 16384 $0.46 48.4

Other benchmarks for DBRX 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 52.8 581 3th
GPQA Diamond 43.6 573 5th
SWE-bench Verified 32.7 572 5th
HumanEval 48.3 583 3th
MATH-500 44.0 583 3th
AIME 2025 34.8 571 5th
LiveCodeBench 33.6 574 4th
IFEval 58.1 582 3th
TruthfulQA 54.9 575 4th
MMMU 48.0 563 6th
Arena Elo 1180.3 576 4th

FAQ

What score does DBRX 1.5B get on HellaSwag?

DBRX 1.5B scores 66.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does DBRX 1.5B rank on HellaSwag?

It ranks #575 of 600 models, in the 4th percentile. The leader is GPT-5.2 Max at 96.1.

Is DBRX 1.5B 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 DBRX 1.5B cost?

DBRX 1.5B costs $0.32 per million input tokens and $1.22 per million output tokens.

Related