# Hidden State Extraction

The Hidden State Extraction feature allows vLLM to save intermediate layer activations from a target model during inference. This is useful for training [EAGLE](eagle.md)-style draft models, knowledge distillation, or offline analysis of model internals.

!!! note
    It is possible to save the last-layer's output hidden states by passing `num_hidden_layers` as a layer id. Note that these are _not_ normalized using the output norm.

## Offline Example

```python
import tempfile

from vllm import LLM, SamplingParams
from vllm.config.kv_transfer import KVTransferConfig
from vllm.distributed.kv_transfer.kv_connector.v1 import (
    example_hidden_states_connector,
)

with tempfile.TemporaryDirectory() as tmpdir:
    llm = LLM(
        model="Qwen/Qwen3-8B",
        enable_chunked_prefill=False,
        speculative_config={
            "method": "extract_hidden_states",
            "num_speculative_tokens": 1,
            "draft_model_config": {
                "hf_config": {
                    "eagle_aux_hidden_state_layer_ids": [1, 2, 3, 4],
                },
            },
        },
        kv_transfer_config=KVTransferConfig(
            kv_connector="ExampleHiddenStatesConnector",
            kv_role="kv_producer",
            kv_connector_extra_config={
                "shared_storage_path": tmpdir,
            },
        ),
    )

    outputs = llm.generate(
        ["The future of AI is"],
        SamplingParams(max_tokens=1),
    )

    for output in outputs:
        path = output.kv_transfer_params["hidden_states_path"]
        obj = example_hidden_states_connector.load_hidden_states(path)
        print(f"token_ids: {obj['token_ids'].shape}")
        print(f"hidden_states: {obj['hidden_states'].shape}")
```

A complete example is available at [`examples/features/speculative_decoding/extract_hidden_states_offline.py`](../../../examples/features/speculative_decoding/extract_hidden_states_offline.py).

## Online Example

For improved performance, it is recommended to use a RAM-mounted file system such as `/dev/shm/` for online usage in which the client cleans up the files soon after they are generated.

```bash
vllm serve Qwen/Qwen3-8B \
    --speculative_config '{"method": "extract_hidden_states", "num_speculative_tokens": 1, "draft_model_config": {"hf_config": {"eagle_aux_hidden_state_layer_ids": [1, 2, 3, 4]}}}' \
    --kv_transfer_config '{"kv_connector": "ExampleHiddenStatesConnector", "kv_role": "kv_producer", "kv_connector_extra_config": {"shared_storage_path": "/dev/shm/hidden_states"}}' \
    --no-enable-chunked-prefill
```

## Configuration

The `kv_connector_extra_config` dict accepts these options:

| Parameter | Default | Description |
| --- | --- | --- |
| `shared_storage_path` | `/tmp` | Directory where hidden state files are saved |
| `num_writer_threads` | `8` | Thread pool size for async disk writes |
| `use_synchronization_lock` | `True` | Use file locks so concurrent readers block until writes complete. Can be disabled for batch generation where synchronization is not needed. |

## Output Format

Each request produces a `.safetensors` file containing:

- **`hidden_states`** — shape `[num_tokens, num_extracted_layers, hidden_size]`
- **`token_ids`** — shape `[num_tokens]`

The file path is returned in `output.kv_transfer_params["hidden_states_path"]`. Use `load_hidden_states()` from the connector module to read the file with proper synchronization.

!!! note
    Chunked prefill is not compatible with this feature and must be disabled.