Knowledge · Databricks

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

DBRX Base scores 74.4 on MMLU-Pro, placing it #343 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
74.4
0–100 scale
Rank
#343
of 600
Percentile
43th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
17.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with DBRX Base 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 Base sits at #343 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 17.2 points. The median model in this index scores 76.1, which puts DBRX Base below the midpoint.

Databricks models average 67.9 on this benchmark. DBRX Base is 6.5 points above that provider line, so it is a stronger result than the average Databricks model.

Among open-weight models, the average is 72.1. DBRX Base is 2.3 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 74.4 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 $2.63 per million input tokens, DBRX Base 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
o4 Nano OpenAI 65536 $8.61 72.0
Llama 3 Anyscale Base Anyscale 65536 $3.23 72.9
Molmo Instruct Allen Institute for AI 32768 $2.53 68.3
Auto Max OpenRouter 8192 $8.41 71.2
DBRX Base Databricks 32768 $2.63 69.1
Llama 3 Novita Base Novita AI 8192 $3.06 70.3
Phi-3.5 Chat Microsoft 16384 $2.64 69.0

Other benchmarks for DBRX Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 66.5 338 44th
SWE-bench Verified 55.0 385 36th
HumanEval 75.9 329 45th
MATH-500 70.9 379 37th
AIME 2025 63.5 363 40th
LiveCodeBench 58.3 384 36th
IFEval 76.7 380 37th
TruthfulQA 70.7 393 35th
HellaSwag 79.4 391 35th
MMMU 69.0 324 46th
Arena Elo 1352.8 359 40th

FAQ

What score does DBRX Base get on MMLU-Pro?

DBRX Base scores 74.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does DBRX Base rank on MMLU-Pro?

It ranks #343 of 600 models, in the 43rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is DBRX Base 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 Base cost?

DBRX Base costs $2.63 per million input tokens and $11.61 per million output tokens.

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