Knowledge · Databricks

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

DBRX Instruct scores 74.2 on MMLU-Pro, placing it #346 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
74.2
0–100 scale
Rank
#346
of 600
Percentile
42th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
17.4
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with DBRX Instruct 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 Instruct sits at #346 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 17.4 points. The median model in this index scores 76.1, which puts DBRX Instruct below the midpoint.

Databricks models average 67.9 on this benchmark. DBRX Instruct is 6.3 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 Instruct is 2.1 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 74.2 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 $3.21 per million input tokens, DBRX Instruct 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
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
DBRX Instruct Databricks 8192 $3.21 72.4
Firesearch Turbo Fireworks AI 16384 $7.58 69.3
Codestral Base Mistral AI 8192 $3.31 73.1

Other benchmarks for DBRX Instruct

BenchmarkScoreRankPercentileRelative
GPQA Diamond 66.6 337 44th
SWE-bench Verified 58.7 346 42th
HumanEval 74.8 346 42th
MATH-500 75.7 308 49th
AIME 2025 67.5 301 50th
LiveCodeBench 65.0 294 51th
IFEval 82.5 259 57th
TruthfulQA 77.6 264 56th
HellaSwag 83.1 315 48th
MMMU 70.2 289 52th
Arena Elo 1374.8 293 51th

FAQ

What score does DBRX Instruct get on MMLU-Pro?

DBRX Instruct scores 74.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does DBRX Instruct rank on MMLU-Pro?

It ranks #346 of 600 models, in the 42nd percentile. The leader is GPT-5.2 Pro at 91.6.

Is DBRX Instruct 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 Instruct cost?

DBRX Instruct costs $3.21 per million input tokens and $15.67 per million output tokens.

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