Multimodal · Databricks

DBRX Base on MMMU: score, rank and what it means

DBRX Base scores 69.0 on MMMU, placing it #324 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
69.0
0–100 scale
Rank
#324
of 600
Percentile
46th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
17.9
points

Score distribution

The chart shows the top 10 models on MMMU, with DBRX Base highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, DBRX Base sits at #324 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 17.9 points. The median model in this index scores 70.0, which puts DBRX Base below the midpoint.

Databricks models average 61.4 on this benchmark. DBRX Base is 7.6 points above that provider line, so it is a stronger result than the average Databricks model.

Among open-weight models, the average is 65.1. DBRX Base is 3.9 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 69.0 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 $2.63 per million input tokens, DBRX Base is below the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DBRX Databricks 65536 $3.29 73.3
Reka Flash Reka AI 128000 $9.95 74.1
Claude Opus 4.5 Nano Anthropic 32768 $9.38 73.3
Llama 3 Modal Instruct Modal 128000 $3.84 75.2
DBRX Base Databricks 32768 $2.63 69.1
DeepSeek-Coder Base DeepSeek 32768 $3.53 74.1
OLMo 2 Chat Allen Institute for AI 16384 $2.94 70.6

Other benchmarks for DBRX Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.4 343 43th
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
Arena Elo 1352.8 359 40th

FAQ

What score does DBRX Base get on MMMU?

DBRX Base scores 69.0 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does DBRX Base rank on MMMU?

It ranks #324 of 600 models, in the 46th percentile. The leader is GPT-5.2 Max at 86.9.

Is DBRX Base good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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