Llama 4 Maverick 1.5B on HellaSwag: score, rank and what it means
Llama 4 Maverick 1.5B scores 70.2 on HellaSwag, placing it #532 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.
Score distribution
The chart shows the top 10 models on HellaSwag, with Llama 4 Maverick 1.5B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 2 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 5 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 8 | Gemini 3 Pro Turbo | Google DeepMind | 400000 | $19.62 | 86.4 |
| 9 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 10 | o4 Pro | OpenAI | 1000000 | $19.37 | 87.3 |
What this score means
On HellaSwag, Llama 4 Maverick 1.5B sits at #532 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 25.9 points. The median model in this index scores 83.6, which puts Llama 4 Maverick 1.5B below the midpoint.
Meta AI models average 80.6 on this benchmark. Llama 4 Maverick 1.5B is 10.4 points below that provider line, so it is a weaker result than the average Meta AI model.
Among small open-weight models, the average is 70.2. Llama 4 Maverick 1.5B is 0.0 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 70.2 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 $0.93 per million input tokens, Llama 4 Maverick 1.5B is below the median input price of $4.00 across the 600 models scored on HellaSwag. 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 |
|---|---|---|---|---|
| Kimi K1.5 1.5B | Moonshot AI | 4096 | $0.75 | 53.2 |
| Llama 3.3 Groq 7B | Groq | 16384 | $1.01 | 56.7 |
| DBRX 8B | Databricks | 4096 | $0.82 | 54.1 |
| Mixtral 7B | Mistral AI | 16384 | $0.70 | 54.1 |
| Llama 4 Maverick 1.5B | Meta AI | 8192 | $0.93 | 55.2 |
| Mixtral Turbo 8B | Together AI | 4096 | $0.75 | 54.1 |
| Llama 3 Lambda 7B | Lambda | 8192 | $0.84 | 55.4 |
Other benchmarks for Llama 4 Maverick 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 59.9 | 530 | 12th | |
| GPQA Diamond | 53.6 | 487 | 19th | |
| SWE-bench Verified | 40.5 | 517 | 14th | |
| HumanEval | 60.6 | 494 | 18th | |
| MATH-500 | 54.6 | 524 | 13th | |
| AIME 2025 | 41.6 | 532 | 11th | |
| LiveCodeBench | 42.1 | 525 | 13th | |
| IFEval | 66.3 | 514 | 14th | |
| TruthfulQA | 61.3 | 517 | 14th | |
| MMMU | 56.5 | 480 | 20th | |
| Arena Elo | 1228.4 | 528 | 12th |
FAQ
What score does Llama 4 Maverick 1.5B get on HellaSwag?
Llama 4 Maverick 1.5B scores 70.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.
How does Llama 4 Maverick 1.5B rank on HellaSwag?
It ranks #532 of 600 models, in the 11th percentile. The leader is GPT-5.2 Max at 96.1.
Is Llama 4 Maverick 1.5B good at HellaSwag?
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 HellaSwag score calculated?
HellaSwag is a commonsense 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 Llama 4 Maverick 1.5B cost?
Llama 4 Maverick 1.5B costs $0.93 per million input tokens and $3.35 per million output tokens.