DeepSeek-V3.2 1.5B on HumanEval: score, rank and what it means
DeepSeek-V3.2 1.5B scores 61.0 on HumanEval, placing it #487 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with DeepSeek-V3.2 1.5B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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 1.5B sits at #487 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 35.8 points. The median model in this index scores 77.4, which puts DeepSeek-V3.2 1.5B below the midpoint.
DeepSeek models average 75.7 on this benchmark. DeepSeek-V3.2 1.5B is 14.7 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 1.5B is 4.3 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 61.0 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 $1.02 per million input tokens, DeepSeek-V3.2 1.5B 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 4 Scout 7B | Meta AI | 32768 | $1.30 | 60.0 |
| Nemotron 4 8B | NVIDIA | 4096 | $1.06 | 57.9 |
| Llama 3.3 Groq 7B | Groq | 16384 | $1.01 | 56.7 |
| Magistral 7B | Mistral AI | 32768 | $1.22 | 58.9 |
| DeepSeek-V3.2 1.5B | DeepSeek | 4096 | $1.02 | 56.9 |
| Fusion Nano | OpenRouter | 8192 | $2.96 | 56.8 |
| Llama 3 Lambda 7B | Lambda | 8192 | $0.84 | 55.4 |
Other benchmarks for DeepSeek-V3.2 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 63.7 | 476 | 21th | |
| GPQA Diamond | 53.6 | 486 | 19th | |
| SWE-bench Verified | 41.4 | 507 | 16th | |
| MATH-500 | 55.4 | 517 | 14th | |
| AIME 2025 | 45.4 | 494 | 18th | |
| LiveCodeBench | 45.5 | 493 | 18th | |
| IFEval | 70.1 | 460 | 23th | |
| TruthfulQA | 61.3 | 516 | 14th | |
| HellaSwag | 72.0 | 496 | 17th | |
| MMMU | 56.3 | 483 | 20th | |
| Arena Elo | 1260.0 | 475 | 21th |
FAQ
What score does DeepSeek-V3.2 1.5B get on HumanEval?
DeepSeek-V3.2 1.5B scores 61.0 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does DeepSeek-V3.2 1.5B rank on HumanEval?
It ranks #487 of 600 models, in the 19th percentile. The leader is GPT-5.2 Pro at 96.8.
Is DeepSeek-V3.2 1.5B 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 1.5B cost?
DeepSeek-V3.2 1.5B costs $1.02 per million input tokens and $5.25 per million output tokens.