Multimodal · Databricks

DBRX 7B on MMMU: score, rank and what it means

DBRX 7B scores 48.2 on MMMU, placing it #562 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
48.2
0–100 scale
Rank
#562
of 600
Percentile
6th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
38.7
points

Score distribution

The chart shows the top 10 models on MMMU, with DBRX 7B 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 7B sits at #562 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 38.7 points. The median model in this index scores 70.0, which puts DBRX 7B below the midpoint.

Databricks models average 61.4 on this benchmark. DBRX 7B is 13.2 points below that provider line, so it is a weaker result than the average Databricks model.

Among small open-weight models, the average is 52.4. DBRX 7B is 4.2 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 48.2 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 $0.65 per million input tokens, DBRX 7B 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
Codestral 1.5B Mistral AI 8192 $0.52 49.9
Mixtral Turbo 1.5B Together AI 4096 $0.31 47.6
Yi-Lightning 1.5B 01.AI 4096 $0.54 50.0
Gemma 3 1.5B Google DeepMind 32768 $0.40 48.9
DBRX 7B Databricks 8192 $0.65 51.9
DBRX 1.5B Databricks 16384 $0.32 47.0
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2

Other benchmarks for DBRX 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.7 517 14th
GPQA Diamond 50.0 523 13th
SWE-bench Verified 35.7 548 9th
HumanEval 54.5 546 9th
MATH-500 50.5 552 8th
AIME 2025 40.7 539 10th
LiveCodeBench 38.4 546 9th
IFEval 62.6 548 9th
TruthfulQA 58.7 542 10th
HellaSwag 70.7 527 12th
Arena Elo 1214.7 539 10th

FAQ

What score does DBRX 7B get on MMMU?

DBRX 7B scores 48.2 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does DBRX 7B rank on MMMU?

It ranks #562 of 600 models, in the 6th percentile. The leader is GPT-5.2 Max at 86.9.

Is DBRX 7B 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 7B cost?

DBRX 7B costs $0.65 per million input tokens and $3.08 per million output tokens.

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