Reasoning · Snowflake

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

Arctic Instruct scores 64.6 on GPQA Diamond, placing it #367 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
64.6
0–100 scale
Rank
#367
of 600
Percentile
39th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
22.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Arctic Instruct 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 Instruct sits at #367 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 22.4 points. The median model in this index scores 68.8, which puts Arctic Instruct below the midpoint.

Snowflake models average 55.6 on this benchmark. Arctic Instruct is 9.0 points above that provider line, so it is a stronger result than the average Snowflake model.

Among open-weight models, the average is 63.6. Arctic Instruct is 1.0 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 64.6 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 $2.83 per million input tokens, Arctic Instruct 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
Phi-4 Base Microsoft 32768 $3.15 71.2
o3 Nano OpenAI 32768 $7.78 70.6
Gemma 3 Base Google DeepMind 65536 $3.09 71.1
Nemotron Nano Instruct NVIDIA 32768 $2.33 67.4
Arctic Instruct Snowflake 65536 $2.83 70.6
Nova Pro Mini Amazon 16384 $7.74 70.6
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7

Other benchmarks for Arctic Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.3 380 37th
SWE-bench Verified 58.3 348 42th
HumanEval 74.1 356 41th
MATH-500 74.3 340 43th
AIME 2025 66.7 318 47th
LiveCodeBench 65.2 288 52th
IFEval 78.9 357 41th
TruthfulQA 74.1 350 42th
HellaSwag 83.6 297 51th
MMMU 64.9 381 37th
Arena Elo 1343.7 375 38th

FAQ

What score does Arctic Instruct get on GPQA Diamond?

Arctic Instruct scores 64.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Arctic Instruct rank on GPQA Diamond?

It ranks #367 of 600 models, in the 39th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Arctic Instruct 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 Instruct cost?

Arctic Instruct costs $2.83 per million input tokens and $13.96 per million output tokens.

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