Knowledge · Databricks

DBRX 1.5B on MMLU-Pro: score, rank and what it means

DBRX 1.5B scores 52.8 on MMLU-Pro, placing it #581 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
52.8
0–100 scale
Rank
#581
of 600
Percentile
3th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
38.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with DBRX 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, DBRX 1.5B sits at #581 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 38.8 points. The median model in this index scores 76.1, which puts DBRX 1.5B below the midpoint.

Databricks models average 67.9 on this benchmark. DBRX 1.5B is 15.1 points below that provider line, so it is a weaker result than the average Databricks model.

Among small open-weight models, the average is 59.8. DBRX 1.5B is 7.0 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 52.8 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 MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
SmolLM3 7B Hugging Face 16384 $0.19 44.3
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
DBRX 1.5B Databricks 16384 $0.32 47.0
Zephyr 7B Hugging Face 32768 $0.23 42.5
Arctic 1.5B Snowflake 32768 $0.15 43.2

Other benchmarks for DBRX 1.5B

BenchmarkScoreRankPercentileRelative
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
HellaSwag 66.2 575 4th
MMMU 48.0 563 6th
Arena Elo 1180.3 576 4th

FAQ

What score does DBRX 1.5B get on MMLU-Pro?

DBRX 1.5B scores 52.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does DBRX 1.5B rank on MMLU-Pro?

It ranks #581 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is DBRX 1.5B good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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.

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