Knowledge · Snowflake

Arctic 7B on MMLU-Pro: score, rank and what it means

Arctic 7B scores 57.7 on MMLU-Pro, placing it #553 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
57.7
0–100 scale
Rank
#553
of 600
Percentile
8th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
33.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Arctic 7B 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, Arctic 7B sits at #553 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 33.9 points. The median model in this index scores 76.1, which puts Arctic 7B below the midpoint.

Snowflake models average 65.2 on this benchmark. Arctic 7B is 7.5 points below that provider line, so it is a weaker result than the average Snowflake model.

Among small open-weight models, the average is 59.8. Arctic 7B is 2.1 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 57.7 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 $0.49 per million input tokens, Arctic 7B 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
Yi-Lightning 1.5B 01.AI 4096 $0.54 50.0
MiniMax-Text 1.5B MiniMax 32768 $0.58 51.5
Llama 3.1 Turbo 1.5B Together AI 16384 $0.46 49.8
Qwen3-Coder 1.5B Alibaba Cloud 32768 $0.76 52.8
Arctic 7B Snowflake 8192 $0.49 50.3
Llama 3.1 Cerebras 1.5B Cerebras 4096 $0.48 50.2
QwQ 1.5B Alibaba Cloud 32768 $0.61 51.6

Other benchmarks for Arctic 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 45.1 567 6th
SWE-bench Verified 34.7 558 7th
HumanEval 51.2 563 6th
MATH-500 51.8 542 10th
AIME 2025 37.7 554 8th
LiveCodeBench 39.2 541 10th
IFEval 63.1 545 9th
TruthfulQA 58.0 547 9th
HellaSwag 67.9 558 7th
MMMU 47.4 569 5th
Arena Elo 1201.2 552 8th

FAQ

What score does Arctic 7B get on MMLU-Pro?

Arctic 7B scores 57.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Arctic 7B rank on MMLU-Pro?

It ranks #553 of 600 models, in the 8th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Arctic 7B 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 Arctic 7B cost?

Arctic 7B costs $0.49 per million input tokens and $2.38 per million output tokens.

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