# Compatible Parameters

TokenSpeed keeps familiar serving parameter names when the operational meaning
is the same. This makes recipes portable while still documenting
TokenSpeed-specific behavior explicitly.

## Directly Aligned

| Parameter | TokenSpeed behavior |
| --- | --- |
| positional `model` | Model path or Hugging Face repo ID. |
| `--model` | Equivalent to positional `model`. |
| `--tokenizer` | Tokenizer path. |
| `--tokenizer-mode` | Tokenizer implementation mode. |
| `--skip-tokenizer-init` | Skip tokenizer initialization. |
| `--load-format` | Weight loading format. |
| `--trust-remote-code` | Allow custom model code from the model repository. |
| `--dtype` | Weight and activation dtype. |
| `--kv-cache-dtype` | KV cache storage dtype. |
| `--quantization` | Weight quantization method. |
| `--quantization-param-path` | KV cache scaling-factor file. |
| `--max-model-len` | Maximum sequence length. |
| `--device` | Device type. TokenSpeed currently serves CUDA. |
| `--served-model-name` | OpenAI-compatible served model name. |
| `--revision` | Model revision. |
| `--download-dir` | Model download directory. |
| `--hf-overrides` | JSON model config overrides. |
| `--host` | HTTP bind host. |
| `--port` | HTTP bind port. |
| `--api-key` | API key for the server. |
| `--chat-template` | Chat template name or path. |
| `--gpu-memory-utilization` | GPU memory fraction used for weights and KV cache. |
| `--max-num-seqs` | Maximum concurrent sequences. |
| `--block-size` | KV cache block size. |
| `--enable-prefix-caching` | Enable prefix cache reuse. |
| `--no-enable-prefix-caching` | Disable prefix cache reuse. |
| `--enforce-eager` | Disable CUDA graph execution. |
| `--max-cudagraph-capture-size` | Largest CUDA graph capture size. |
| `--tensor-parallel-size`, `--tp` | Set attention tensor parallel size. |
| `--data-parallel-size` | Data parallel size. |
| `--enable-expert-parallel` | Enable expert parallelism. |
| `--speculative-config` | JSON speculative decoding config. |
| `--kv-events-config` | JSON KV cache event publisher config; the vLLM-style `enable_kv_cache_events` field is accepted and defaults to ZMQ when enabled. |
| `--tool-call-parser` | OpenAI-compatible tool-call parser. |
| `--reasoning-parser` | Reasoning-output parser. |

## Similar But Not Identical

| Recipe parameter | TokenSpeed parameter | Difference |
| --- | --- | --- |
| `--max-num-batched-tokens` | `--chunked-prefill-size` | TokenSpeed uses this as the scheduler per-iteration issue budget. |
| `--max-num-batched-tokens` | `--max-total-tokens` | TokenSpeed uses this for the global token pool size override. |
| `--tensor-parallel-size`, `--tp` | `--attn-tp-size` | The familiar alias maps to attention TP. TokenSpeed can split attention, dense, and MoE TP. |
| `--expert-parallel-size` | `--expert-parallel-size`, `--ep-size` | TokenSpeed supports the familiar name and its existing short form. |
| `--attention-backend` | `--attention-backend` | Name is aligned; available backend values are TokenSpeed-specific. |
| `--moe-backend` | `--moe-backend` | Name is aligned; available backend values are TokenSpeed-specific. |

## Recipe Translation Notes

- Use `tokenspeed serve` as the launcher.
- Pass the model path positionally, then keep `--trust-remote-code`, `--max-model-len`, `--kv-cache-dtype`, `--gpu-memory-utilization`, `--max-num-seqs`, `--tensor-parallel-size`, `--reasoning-parser`, and `--tool-call-parser` when the model needs them.
- Review `--max-num-batched-tokens` before copying it. TokenSpeed usually wants `--chunked-prefill-size` for per-iteration scheduling.
- Review backend names. TokenSpeed backends are optimized for its runtime and kernel packages.
- Keep TokenSpeed-specific `--attn-tp-size`, `--moe-tp-size`, `--disaggregation-*`, and `--kvstore-*` only when the deployment needs those features.