Coding · DeepSeek

DeepSeek-V3.2 8B on HumanEval: score, rank and what it means

DeepSeek-V3.2 8B scores 69.7 on HumanEval, placing it #398 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
69.7
0–100 scale
Rank
#398
of 600
Percentile
34th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
27.1
points

Score distribution

The chart shows the top 10 models on HumanEval, with DeepSeek-V3.2 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, DeepSeek-V3.2 8B sits at #398 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 27.1 points. The median model in this index scores 77.4, which puts DeepSeek-V3.2 8B below the midpoint.

DeepSeek models average 75.7 on this benchmark. DeepSeek-V3.2 8B is 6.0 points below that provider line, so it is a weaker result than the average DeepSeek model.

Among small open-weight models, the average is 56.7. DeepSeek-V3.2 8B is 13.0 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 69.7 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 $2.02 per million input tokens, DeepSeek-V3.2 8B is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
StableLM 2 Stability AI 8192 $1.91 65.0
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Molmo Base Allen Institute for AI 4096 $2.02 65.0
DeepSeek-R1 8B DeepSeek 16384 $1.87 64.3
DeepSeek-V3.2 8B DeepSeek 32768 $2.02 66.2
Nemotron Nano NVIDIA 8192 $2.24 66.6
StableLM 2 Chat Stability AI 8192 $1.79 64.6

Other benchmarks for DeepSeek-V3.2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 72.4 378 37th
GPQA Diamond 58.8 419 30th
SWE-bench Verified 55.2 382 36th
MATH-500 66.7 410 32th
AIME 2025 56.4 409 32th
LiveCodeBench 58.9 379 37th
IFEval 76.0 388 35th
TruthfulQA 71.6 386 36th
HellaSwag 77.4 409 32th
MMMU 65.4 377 37th
Arena Elo 1308.4 410 32th

FAQ

What score does DeepSeek-V3.2 8B get on HumanEval?

DeepSeek-V3.2 8B scores 69.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does DeepSeek-V3.2 8B rank on HumanEval?

It ranks #398 of 600 models, in the 34th percentile. The leader is GPT-5.2 Pro at 96.8.

Is DeepSeek-V3.2 8B good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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-V3.2 8B cost?

DeepSeek-V3.2 8B costs $2.02 per million input tokens and $9.37 per million output tokens.

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