Claude Haiku 4.5 Nano on MATH-500: score, rank and what it means
Claude Haiku 4.5 Nano scores 71.8 on MATH-500, placing it #369 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 Claude Haiku 4.5 Nano 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, Claude Haiku 4.5 Nano sits at #369 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 24.9 points. The median model in this index scores 76.0, which puts Claude Haiku 4.5 Nano below the midpoint.
Anthropic models average 85.3 on this benchmark. Claude Haiku 4.5 Nano is 13.5 points below that provider line, so it is a weaker result than the average Anthropic model.
Among mid-range models, the average is 70.0. Claude Haiku 4.5 Nano is 1.8 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 71.8 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 $6.47 per million input tokens, Claude Haiku 4.5 Nano is above 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 |
|---|---|---|---|---|
| OLMo 2 Instruct | Allen Institute for AI | 32768 | $3.03 | 71.7 |
| Molmo | Allen Institute for AI | 32768 | $2.49 | 68.5 |
| Llama 3 Novita Base | Novita AI | 8192 | $3.06 | 70.3 |
| Phi-4 Base | Microsoft | 32768 | $3.15 | 71.2 |
| Claude Haiku 4.5 Nano | Anthropic | 8192 | $6.47 | 68.7 |
| Arctic Base | Snowflake | 32768 | $2.27 | 67.5 |
| ERNIE 4.0 Mini | Baidu | 32768 | $7.11 | 68.8 |
Other benchmarks for Claude Haiku 4.5 Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 73.9 | 355 | 41th | |
| GPQA Diamond | 64.5 | 369 | 39th | |
| SWE-bench Verified | 56.9 | 367 | 39th | |
| HumanEval | 71.0 | 388 | 35th | |
| AIME 2025 | 63.5 | 361 | 40th | |
| LiveCodeBench | 59.8 | 369 | 39th | |
| IFEval | 78.2 | 363 | 40th | |
| TruthfulQA | 71.6 | 385 | 36th | |
| HellaSwag | 80.5 | 378 | 37th | |
| MMMU | 64.3 | 386 | 36th | |
| Arena Elo | 1332.1 | 385 | 36th |
FAQ
What score does Claude Haiku 4.5 Nano get on MATH-500?
Claude Haiku 4.5 Nano scores 71.8 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Claude Haiku 4.5 Nano rank on MATH-500?
It ranks #369 of 600 models, in the 39th percentile. The leader is GPT-5.2 Max at 96.7.
Is Claude Haiku 4.5 Nano good at MATH-500?
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 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 Claude Haiku 4.5 Nano cost?
Claude Haiku 4.5 Nano costs $6.47 per million input tokens and $27.98 per million output tokens.