Mathematics · DeepSeek

DeepSeek-Coder Chat on MATH-500: score, rank and what it means

DeepSeek-Coder Chat scores 81.6 on MATH-500, placing it #174 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
81.6
0–100 scale
Rank
#174
of 600
Percentile
71th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
15.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with DeepSeek-Coder Chat 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, DeepSeek-Coder Chat sits at #174 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 15.1 points. The median model in this index scores 76.0, which puts DeepSeek-Coder Chat above the midpoint.

DeepSeek models average 74.2 on this benchmark. DeepSeek-Coder Chat is 7.4 points above that provider line, so it is a stronger result than the average DeepSeek model.

Among coding models, the average is 71.0. DeepSeek-Coder Chat is 10.6 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 81.6 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 $4.20 per million input tokens, DeepSeek-Coder Chat is above 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
GLM-4.5 Zhipu AI 200000 $4.55 78.2
Kimi K1.5 Chat Moonshot AI 128000 $5.11 80.2
Magistral Instruct Mistral AI 65536 $4.48 78.4
Reka Flash Max Reka AI 32768 $11.17 75.9
DeepSeek-Coder Chat DeepSeek 200000 $4.20 77.3
Mistral Large 3 Chat Mistral AI 1000000 $4.90 79.1
Llama 3.1 Turbo Chat Together AI 200000 $3.95 76.1

Other benchmarks for DeepSeek-Coder Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.9 244 59th
GPQA Diamond 74.0 168 72th
SWE-bench Verified 64.5 221 63th
HumanEval 82.5 173 71th
AIME 2025 70.1 255 58th
LiveCodeBench 69.6 199 67th
IFEval 85.8 163 73th
TruthfulQA 79.9 180 70th
HellaSwag 88.1 137 77th
MMMU 76.5 124 79th
Arena Elo 1414.5 170 72th

FAQ

What score does DeepSeek-Coder Chat get on MATH-500?

DeepSeek-Coder Chat scores 81.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does DeepSeek-Coder Chat rank on MATH-500?

It ranks #174 of 600 models, in the 71st percentile. The leader is GPT-5.2 Max at 96.7.

Is DeepSeek-Coder Chat 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 DeepSeek-Coder Chat cost?

DeepSeek-Coder Chat costs $4.20 per million input tokens and $19.27 per million output tokens.

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