Commonsense · Databricks

DBRX Instruct on HellaSwag: score, rank and what it means

DBRX Instruct scores 83.1 on HellaSwag, placing it #315 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
83.1
0–100 scale
Rank
#315
of 600
Percentile
48th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
13.0
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, DBRX Instruct sits at #315 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 13.0 points. The median model in this index scores 83.6, which puts DBRX Instruct below the midpoint.

Databricks models average 76.4 on this benchmark. DBRX Instruct is 6.7 points above that provider line, so it is a stronger result than the average Databricks model.

Among open-weight models, the average is 80.2. DBRX Instruct is 2.9 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 83.1 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Codestral Base Mistral AI 8192 $3.31 73.1
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Llama 3 Hyperbolic Base Hyperbolic 32768 $3.02 71.1
Claude 3.7 Sonnet Mini Anthropic 32768 $9.74 73.0
DBRX Instruct Databricks 8192 $3.21 72.4
Firefunction Reasoning Fireworks AI 8192 $9.08 72.5
Llama 3 Modal Chat Modal 65536 $3.55 73.3

Other benchmarks for DBRX Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.2 346 42th
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
MMMU 70.2 289 52th
Arena Elo 1374.8 293 51th

FAQ

What score does DBRX Instruct get on HellaSwag?

DBRX Instruct scores 83.1 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does DBRX Instruct rank on HellaSwag?

It ranks #315 of 600 models, in the 48th percentile. The leader is GPT-5.2 Max at 96.1.

Is DBRX Instruct good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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