Reasoning · Snowflake

Arctic 7B on GPQA Diamond: score, rank and what it means

Arctic 7B scores 45.1 on GPQA Diamond, placing it #567 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
45.1
0–100 scale
Rank
#567
of 600
Percentile
6th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
41.9
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Arctic 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Arctic 7B sits at #567 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 41.9 points. The median model in this index scores 68.8, which puts Arctic 7B below the midpoint.

Snowflake models average 55.6 on this benchmark. Arctic 7B is 10.5 points below that provider line, so it is a weaker result than the average Snowflake model.

Among small open-weight models, the average is 49.3. Arctic 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 45.1 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 $0.49 per million input tokens, Arctic 7B is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-Coder 1.5B DeepSeek 16384 $0.58 51.0
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Mixtral Turbo 1.5B Together AI 4096 $0.31 47.6
Seed-OSS 1.5B ByteDance 4096 $0.45 49.8
Arctic 7B Snowflake 8192 $0.49 50.3
Llama 3 Baseten 1.5B Baseten 4096 $0.42 48.2
Mistral Small 3 1.5B Mistral AI 32768 $0.42 49.2

Other benchmarks for Arctic 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 57.7 553 8th
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 GPQA Diamond?

Arctic 7B scores 45.1 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Arctic 7B rank on GPQA Diamond?

It ranks #567 of 600 models, in the 6th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Arctic 7B good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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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