Mathematics · Snowflake

Arctic on MATH-500: score, rank and what it means

Arctic scores 70.5 on MATH-500, placing it #382 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
70.5
0–100 scale
Rank
#382
of 600
Percentile
36th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
26.2
points

Score distribution

The chart shows the top 10 models on MATH-500, with Arctic highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Arctic sits at #382 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 26.2 points. The median model in this index scores 76.0, which puts Arctic below the midpoint.

Snowflake models average 62.3 on this benchmark. Arctic is 8.2 points above that provider line, so it is a stronger result than the average Snowflake model.

Among open-weight models, the average is 70.8. Arctic is 0.3 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 70.5 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 $2.72 per million input tokens, Arctic is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Yi-Large Base 01.AI 16384 $2.78 70.3
DBRX Base Databricks 32768 $2.63 69.1
Firesearch Reasoning Fireworks AI 32768 $7.74 69.0
Mixtral Groq Base Groq 32768 $2.66 68.4
Arctic Snowflake 8192 $2.72 68.8
Doubao 1.5 Pro Nano ByteDance 16384 $5.78 66.6
Firesearch Pro Fireworks AI 32768 $7.67 70.4

Other benchmarks for Arctic

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.4 377 37th
GPQA Diamond 65.3 354 41th
SWE-bench Verified 54.2 391 35th
HumanEval 73.2 370 38th
AIME 2025 64.6 343 43th
LiveCodeBench 61.6 354 41th
IFEval 79.0 354 41th
TruthfulQA 71.5 387 36th
HellaSwag 80.5 377 37th
MMMU 63.8 391 35th
Arena Elo 1345.7 370 38th

FAQ

What score does Arctic get on MATH-500?

Arctic scores 70.5 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Arctic rank on MATH-500?

It ranks #382 of 600 models, in the 36th percentile. The leader is GPT-5.2 Max at 96.7.

Is Arctic good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 cost?

Arctic costs $2.72 per million input tokens and $10.57 per million output tokens.

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