Embed 4 Pro on MATH-500: score, rank and what it means
Embed 4 Pro scores 63.8 on MATH-500, placing it #427 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 Embed 4 Pro 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, Embed 4 Pro sits at #427 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 32.9 points. The median model in this index scores 76.0, which puts Embed 4 Pro below the midpoint.
Cohere models average 70.8 on this benchmark. Embed 4 Pro is 7.0 points below that provider line, so it is a weaker result than the average Cohere model.
Among mid-range models, the average is 70.0. Embed 4 Pro is 6.2 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 63.8 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 $5.05 per million input tokens, Embed 4 Pro 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 |
|---|---|---|---|---|
| Llama 4 Maverick 8B | Meta AI | 4096 | $1.64 | 63.4 |
| DeepSeek-R1 7B | DeepSeek | 32768 | $1.79 | 63.0 |
| GPT-NeoX | EleutherAI | 16384 | $1.57 | 61.7 |
| StableLM 2 Base | Stability AI | 8192 | $1.49 | 61.9 |
| Embed 4 Pro | Cohere | 4096 | $5.05 | 63.5 |
| Pythia | EleutherAI | 32768 | $1.29 | 59.8 |
| Pythia Instruct | EleutherAI | 8192 | $1.41 | 60.8 |
Other benchmarks for Embed 4 Pro
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 69.3 | 404 | 33th | |
| GPQA Diamond | 61.3 | 397 | 34th | |
| SWE-bench Verified | 52.0 | 405 | 33th | |
| HumanEval | 68.0 | 414 | 31th | |
| AIME 2025 | 53.2 | 431 | 28th | |
| LiveCodeBench | 52.2 | 426 | 29th | |
| IFEval | 72.8 | 419 | 30th | |
| TruthfulQA | 66.8 | 433 | 28th | |
| HellaSwag | 78.6 | 397 | 34th | |
| MMMU | 60.5 | 423 | 30th | |
| Arena Elo | 1316.6 | 399 | 34th |
FAQ
What score does Embed 4 Pro get on MATH-500?
Embed 4 Pro scores 63.8 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Embed 4 Pro rank on MATH-500?
It ranks #427 of 600 models, in the 29th percentile. The leader is GPT-5.2 Max at 96.7.
Is Embed 4 Pro 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 Embed 4 Pro cost?
Embed 4 Pro costs $5.05 per million input tokens and $19.40 per million output tokens.