Llama 3 Replicate Instruct on MATH-500: score, rank and what it means
Llama 3 Replicate Instruct scores 79.9 on MATH-500, placing it #213 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Llama 3 Replicate Instruct 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-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 3 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 4 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
| 5 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 6 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 7 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 8 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 9 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 10 | Claude Opus 4.5 Turbo | Anthropic | 2000000 | $19.57 | 85.7 |
What this score means
On MATH-500, Llama 3 Replicate Instruct sits at #213 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 16.8 points. The median model in this index scores 76.0, which puts Llama 3 Replicate Instruct above the midpoint.
Replicate models average 68.1 on this benchmark. Llama 3 Replicate Instruct is 11.8 points above that provider line, so it is a stronger result than the average Replicate model.
Among multimodal models, the average is 81.3. Llama 3 Replicate Instruct is 1.4 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 79.9 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 $3.71 per million input tokens, Llama 3 Replicate Instruct is below the median input price of $4.00 across the 600 models scored on MATH-500. 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 |
|---|---|---|---|---|
| DeepSeek-Coder | DeepSeek | 32768 | $4.55 | 78.1 |
| GPT-5.1 Mini | OpenAI | 128000 | $12.19 | 77.7 |
| Kimi K1.5 Base | Moonshot AI | 65536 | $4.34 | 77.4 |
| Llama 3 Novita Instruct | Novita AI | 32768 | $3.94 | 75.6 |
| Llama 3 Replicate Instruct | Replicate | 128000 | $3.71 | 75.1 |
| Llama 3 Lambda | Lambda | 65536 | $3.90 | 75.6 |
| Llama 3.1 Turbo | Together AI | 200000 | $4.17 | 76.8 |
Other benchmarks for Llama 3 Replicate Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 75.8 | 309 | 49th | |
| GPQA Diamond | 72.7 | 205 | 66th | |
| SWE-bench Verified | 62.4 | 269 | 55th | |
| HumanEval | 80.5 | 221 | 63th | |
| AIME 2025 | 66.1 | 329 | 45th | |
| LiveCodeBench | 65.9 | 275 | 54th | |
| IFEval | 83.7 | 220 | 63th | |
| TruthfulQA | 78.7 | 228 | 62th | |
| HellaSwag | 86.3 | 205 | 66th | |
| MMMU | 74.4 | 174 | 71th | |
| Arena Elo | 1377.7 | 281 | 53th |
FAQ
What score does Llama 3 Replicate Instruct get on MATH-500?
Llama 3 Replicate Instruct scores 79.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Llama 3 Replicate Instruct rank on MATH-500?
It ranks #213 of 600 models, in the 65th percentile. The leader is GPT-5.2 Max at 96.7.
Is Llama 3 Replicate Instruct good at MATH-500?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the MATH-500 score calculated?
MATH-500 is a mathematics 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 Replicate Instruct cost?
Llama 3 Replicate Instruct costs $3.71 per million input tokens and $19.99 per million output tokens.