Llama 3.3 Groq 7B on LiveCodeBench: score, rank and what it means
Llama 3.3 Groq 7B scores 44.7 on LiveCodeBench, placing it #502 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.
Score distribution
The chart shows the top 10 models on LiveCodeBench, with Llama 3.3 Groq 7B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 2 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 3 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | Grok 4 Turbo | xAI | 1000000 | $19.21 | 86.7 |
| 6 | GPT-5.1 Turbo | OpenAI | 2000000 | $19.19 | 86.1 |
| 7 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 8 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 9 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On LiveCodeBench, Llama 3.3 Groq 7B sits at #502 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 40.4 points. The median model in this index scores 64.7, which puts Llama 3.3 Groq 7B below the midpoint.
Groq models average 55.6 on this benchmark. Llama 3.3 Groq 7B is 10.9 points below that provider line, so it is a weaker result than the average Groq model.
Among small open-weight models, the average is 41.2. Llama 3.3 Groq 7B is 3.5 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 44.7 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 $1.01 per million input tokens, Llama 3.3 Groq 7B is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. 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 |
|---|---|---|---|---|
| Pythia Chat | EleutherAI | 4096 | $1.31 | 59.1 |
| Llama 3.1 7B | Meta AI | 8192 | $1.01 | 57.4 |
| Command R+ 7B | Cohere | 8192 | $0.95 | 56.2 |
| Seed-OSS 7B | ByteDance | 8192 | $0.85 | 55.5 |
| Llama 3.3 Groq 7B | Groq | 16384 | $1.01 | 56.7 |
| Hunyuan-Large 7B | Tencent | 32768 | $1.08 | 57.7 |
| Llama 3 Baseten 8B | Baseten | 4096 | $1.02 | 57.0 |
Other benchmarks for Llama 3.3 Groq 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 64.0 | 472 | 21th | |
| GPQA Diamond | 55.0 | 463 | 23th | |
| SWE-bench Verified | 40.9 | 511 | 15th | |
| HumanEval | 61.1 | 485 | 19th | |
| MATH-500 | 56.5 | 502 | 16th | |
| AIME 2025 | 45.3 | 497 | 17th | |
| IFEval | 65.7 | 524 | 13th | |
| TruthfulQA | 64.0 | 469 | 22th | |
| HellaSwag | 70.5 | 529 | 12th | |
| MMMU | 56.0 | 488 | 19th | |
| Arena Elo | 1240.6 | 511 | 15th |
FAQ
What score does Llama 3.3 Groq 7B get on LiveCodeBench?
Llama 3.3 Groq 7B scores 44.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does Llama 3.3 Groq 7B rank on LiveCodeBench?
It ranks #502 of 600 models, in the 16th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is Llama 3.3 Groq 7B good at LiveCodeBench?
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 LiveCodeBench score calculated?
LiveCodeBench 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 Llama 3.3 Groq 7B cost?
Llama 3.3 Groq 7B costs $1.01 per million input tokens and $3.60 per million output tokens.