Mathematics · ByteDance

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

Seed-OSS scores 79.2 on MATH-500, placing it #230 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
79.2
0–100 scale
Rank
#230
of 600
Percentile
62th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
17.5
points

Score distribution

The chart shows the top 10 models on MATH-500, with Seed-OSS 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, Seed-OSS sits at #230 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 17.5 points. The median model in this index scores 76.0, which puts Seed-OSS above the midpoint.

ByteDance models average 74.2 on this benchmark. Seed-OSS is 5.0 points above that provider line, so it is a stronger result than the average ByteDance model.

Among multimodal models, the average is 81.3. Seed-OSS 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 79.2 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 $3.74 per million input tokens, Seed-OSS 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
Llama 3 Novita Novita AI 128000 $3.70 74.4
Llama 3.3 Groq Instruct Groq 65536 $4.08 76.7
Llama 3 Hyperbolic Chat Hyperbolic 200000 $3.64 75.1
Reka Flash Pro Reka AI 200000 $10.82 75.2
Seed-OSS ByteDance 32768 $3.74 75.3
ERNIE 4.0 Reasoning Baidu 65536 $12.20 77.8
Llama 3 Modal Modal 32768 $3.82 74.9

Other benchmarks for Seed-OSS

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.6 193 68th
GPQA Diamond 72.6 209 65th
SWE-bench Verified 62.8 260 57th
HumanEval 76.9 309 49th
AIME 2025 74.2 176 71th
LiveCodeBench 67.6 237 61th
IFEval 81.6 285 53th
TruthfulQA 77.1 279 54th
HellaSwag 83.5 307 49th
MMMU 73.5 206 66th
Arena Elo 1376.3 287 52th

FAQ

What score does Seed-OSS get on MATH-500?

Seed-OSS scores 79.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Seed-OSS rank on MATH-500?

It ranks #230 of 600 models, in the 62nd percentile. The leader is GPT-5.2 Max at 96.7.

Is Seed-OSS good at MATH-500?

Yes, relative to the index: it is above the median and inside the top half of scores. 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 Seed-OSS cost?

Seed-OSS costs $3.74 per million input tokens and $19.36 per million output tokens.

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