Instruction following · Databricks

DBRX Chat on IFEval: score, rank and what it means

DBRX Chat scores 78.6 on IFEval, placing it #361 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
78.6
0–100 scale
Rank
#361
of 600
Percentile
40th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
17.5
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, DBRX Chat sits at #361 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 17.5 points. The median model in this index scores 81.2, which puts DBRX Chat below the midpoint.

Databricks models average 72.2 on this benchmark. DBRX Chat is 6.4 points above that provider line, so it is a stronger result than the average Databricks model.

Among open-weight models, the average is 77.0. DBRX Chat is 1.6 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 78.6 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 $3.07 per million input tokens, DBRX Chat is below the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Arctic Instruct Snowflake 65536 $2.83 70.6
ERNIE 4.5 Mini Baidu 32768 $8.62 71.0
Firefunction Fireworks AI 16384 $8.16 72.3
Mixtral Turbo Together AI 65536 $3.20 72.4
DBRX Chat Databricks 65536 $3.07 71.7
Auto Reasoning OpenRouter 65536 $8.39 71.5
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7

Other benchmarks for DBRX Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.2 326 46th
GPQA Diamond 67.8 313 48th
SWE-bench Verified 60.0 327 46th
HumanEval 73.6 364 39th
MATH-500 73.2 354 41th
AIME 2025 67.4 305 49th
LiveCodeBench 64.4 307 49th
TruthfulQA 76.9 285 53th
HellaSwag 80.8 374 38th
MMMU 70.4 283 53th
Arena Elo 1372.7 307 49th

FAQ

What score does DBRX Chat get on IFEval?

DBRX Chat scores 78.6 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does DBRX Chat rank on IFEval?

It ranks #361 of 600 models, in the 40th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is DBRX Chat good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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 Chat cost?

DBRX Chat costs $3.07 per million input tokens and $16.42 per million output tokens.

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