Embed 4 Max on HellaSwag: score, rank and what it means
Embed 4 Max scores 76.9 on HellaSwag, placing it #417 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 Embed 4 Max 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, Embed 4 Max sits at #417 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 19.2 points. The median model in this index scores 83.6, which puts Embed 4 Max below the midpoint.
Cohere models average 79.9 on this benchmark. Embed 4 Max is 3.0 points below that provider line, so it is a weaker result than the average Cohere model.
Among mid-range models, the average is 79.8. Embed 4 Max is 2.9 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 76.9 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 $5.68 per million input tokens, Embed 4 Max is above 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 |
|---|---|---|---|---|
| StableLM 2 | Stability AI | 8192 | $1.91 | 65.0 |
| Command A Nano | Cohere | 8192 | $5.90 | 66.3 |
| Embed 4 Turbo | Cohere | 4096 | $5.13 | 64.0 |
| Qwen3 7B | Alibaba Cloud | 32768 | $1.37 | 59.8 |
| Embed 4 Max | Cohere | 8192 | $5.68 | 66.1 |
| Llama 4 Maverick 8B | Meta AI | 4096 | $1.64 | 63.4 |
| Qwen3-Coder 8B | Alibaba Cloud | 32768 | $1.43 | 61.3 |
Other benchmarks for Embed 4 Max
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 72.5 | 375 | 38th | |
| GPQA Diamond | 59.0 | 415 | 31th | |
| SWE-bench Verified | 55.1 | 383 | 36th | |
| HumanEval | 69.6 | 401 | 33th | |
| MATH-500 | 64.8 | 420 | 30th | |
| AIME 2025 | 61.5 | 377 | 37th | |
| LiveCodeBench | 58.2 | 386 | 36th | |
| IFEval | 75.3 | 395 | 34th | |
| TruthfulQA | 68.3 | 411 | 32th | |
| MMMU | 66.1 | 370 | 38th | |
| Arena Elo | 1326.3 | 392 | 35th |
FAQ
What score does Embed 4 Max get on HellaSwag?
Embed 4 Max scores 76.9 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.
How does Embed 4 Max rank on HellaSwag?
It ranks #417 of 600 models, in the 31st percentile. The leader is GPT-5.2 Max at 96.1.
Is Embed 4 Max 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 Embed 4 Max cost?
Embed 4 Max costs $5.68 per million input tokens and $21.60 per million output tokens.