DeepSeek-R1 1.5B on IFEval: score, rank and what it means
DeepSeek-R1 1.5B scores 66.6 on IFEval, placing it #506 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.
Score distribution
The chart shows the top 10 models on IFEval, with DeepSeek-R1 1.5B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 2 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 6 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 7 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
| 8 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 9 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 10 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
What this score means
On IFEval, DeepSeek-R1 1.5B sits at #506 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 29.5 points. The median model in this index scores 81.2, which puts DeepSeek-R1 1.5B below the midpoint.
DeepSeek models average 80.3 on this benchmark. DeepSeek-R1 1.5B is 13.7 points below that provider line, so it is a weaker result than the average DeepSeek model.
Among small open-weight models, the average is 64.9. DeepSeek-R1 1.5B is 1.7 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 66.6 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 $1.04 per million input tokens, DeepSeek-R1 1.5B is below the median input price of $4.00 across the 600 models scored on IFEval. 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 3 Lambda 7B | Lambda | 8192 | $0.84 | 55.4 |
| Mistral Large 3 1.5B | Mistral AI | 32768 | $0.82 | 55.4 |
| Llama 3 Modal 7B | Modal | 4096 | $0.88 | 55.2 |
| Yi-Large 8B | 01.AI | 32768 | $0.88 | 56.1 |
| DeepSeek-R1 1.5B | DeepSeek | 16384 | $1.04 | 56.6 |
| Mixtral Turbo 8B | Together AI | 4096 | $0.75 | 54.1 |
| Auto Nano | OpenRouter | 4096 | $2.83 | 57.1 |
Other benchmarks for DeepSeek-R1 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 60.7 | 518 | 14th | |
| GPQA Diamond | 54.3 | 475 | 21th | |
| SWE-bench Verified | 45.2 | 464 | 23th | |
| HumanEval | 59.7 | 508 | 15th | |
| MATH-500 | 58.5 | 484 | 19th | |
| AIME 2025 | 42.7 | 527 | 12th | |
| LiveCodeBench | 42.9 | 516 | 14th | |
| TruthfulQA | 61.4 | 514 | 14th | |
| HellaSwag | 74.2 | 452 | 25th | |
| MMMU | 56.2 | 484 | 19th | |
| Arena Elo | 1250.5 | 490 | 18th |
FAQ
What score does DeepSeek-R1 1.5B get on IFEval?
DeepSeek-R1 1.5B scores 66.6 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.
How does DeepSeek-R1 1.5B rank on IFEval?
It ranks #506 of 600 models, in the 16th percentile. The leader is Claude Opus 4.5 Pro at 96.1.
Is DeepSeek-R1 1.5B good at IFEval?
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 IFEval score calculated?
IFEval is a instruction following 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-R1 1.5B cost?
DeepSeek-R1 1.5B costs $1.04 per million input tokens and $5.02 per million output tokens.