Production Metrics

vLLM exposes a number of metrics that can be used to monitor the health of the system. These metrics are exposed via the /metrics endpoint on the vLLM OpenAI compatible API server.

You can start the server using Python, or using Docker:

vllm serve unsloth/Llama-3.2-1B-Instruct

Then query the endpoint to get the latest metrics from the server:

Output

$ curl http://0.0.0.0:8000/metrics

# HELP vllm:iteration_tokens_total Histogram of number of tokens per engine_step.
# TYPE vllm:iteration_tokens_total histogram
vllm:iteration_tokens_total_sum{model_name="unsloth/Llama-3.2-1B-Instruct"} 0.0
vllm:iteration_tokens_total_bucket{le="1.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="8.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="16.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="32.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="64.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="128.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="256.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
vllm:iteration_tokens_total_bucket{le="512.0",model_name="unsloth/Llama-3.2-1B-Instruct"} 3.0
...

The following metrics are exposed:

General Metrics

Metric Name	Type	Description
vllm:corrupted_requests	Counter	Corrupted requests, in terms of total number of requests with NaNs in logits.
vllm:external_prefix_cache_hits	Counter	External prefix cache hits from KV connector cross-instance cache sharing, in terms of number of cached tokens.
vllm:external_prefix_cache_queries	Counter	External prefix cache queries from KV connector cross-instance cache sharing, in terms of number of queried tokens.
vllm:generation_tokens	Counter	Number of generation tokens processed.
vllm:mm_cache_hits	Counter	Multi-modal cache hits, in terms of number of cached items.
vllm:mm_cache_queries	Counter	Multi-modal cache queries, in terms of number of queried items.
vllm:num_preemptions	Counter	Cumulative number of preemption from the engine.
vllm:prefix_cache_hits	Counter	Prefix cache hits, in terms of number of cached tokens.
vllm:prefix_cache_queries	Counter	Prefix cache queries, in terms of number of queried tokens.
vllm:prompt_tokens	Counter	Number of prefill tokens processed.
vllm:prompt_tokens_by_source	Counter	Number of prompt tokens by source.
vllm:prompt_tokens_cached	Counter	Number of cached prompt tokens (local + external).
vllm:request_success	Counter	Count of successfully processed requests.
vllm:engine_sleep_state	Gauge	Engine sleep state; awake = 0 means engine is sleeping; awake = 1 means engine is awake; weights_offloaded = 1 means sleep level 1; discard_all = 1 means sleep level 2.
vllm:kv_cache_usage_perc	Gauge	KV-cache usage. 1 means 100 percent usage.
vllm:lora_requests_info	Gauge	Running stats on lora requests.
vllm:num_requests_running	Gauge	Number of requests in model execution batches.
vllm:num_requests_waiting	Gauge	Number of requests waiting to be processed.
vllm:num_requests_waiting_by_reason	Gauge	Number of waiting requests by reason. Reason labels: 'capacity' = waiting for scheduling capacity; 'deferred' = deferred by transient constraints (LoRA budget, KV transfer, blocked status). Sum of all reasons equals vllm:num_requests_waiting.
vllm:e2e_request_latency_seconds	Histogram	Histogram of e2e request latency in seconds.
vllm:inter_token_latency_seconds	Histogram	Histogram of inter-token latency in seconds.
vllm:iteration_tokens_total	Histogram	Histogram of number of tokens per engine_step.
vllm:kv_block_idle_before_evict_seconds	Histogram	Histogram of idle time before KV cache block eviction. Sampled metrics (controlled by --kv-cache-metrics-sample).
vllm:kv_block_lifetime_seconds	Histogram	Histogram of KV cache block lifetime from allocation to eviction. Sampled metrics (controlled by --kv-cache-metrics-sample).
vllm:kv_block_reuse_gap_seconds	Histogram	Histogram of time gaps between consecutive KV cache block accesses. Only the most recent accesses are recorded (ring buffer). Sampled metrics (controlled by --kv-cache-metrics-sample).
vllm:request_decode_time_seconds	Histogram	Histogram of time spent in DECODE phase for request.
vllm:request_generation_tokens	Histogram	Number of generation tokens processed.
vllm:request_inference_time_seconds	Histogram	Histogram of time spent in RUNNING phase for request.
vllm:request_max_num_generation_tokens	Histogram	Histogram of maximum number of requested generation tokens.
vllm:request_num_preemptions	Histogram	Histogram of the number of times a request was preempted.
vllm:request_params_max_tokens	Histogram	Histogram of the max_tokens request parameter.
vllm:request_params_n	Histogram	Histogram of the n request parameter.
vllm:request_prefill_kv_computed_tokens	Histogram	Histogram of new KV tokens computed during prefill (excluding cached tokens).
vllm:request_prefill_time_seconds	Histogram	Histogram of time spent in PREFILL phase for request.
vllm:request_prompt_tokens	Histogram	Number of prefill tokens processed.
vllm:request_queue_time_seconds	Histogram	Histogram of time spent in WAITING phase for request.
vllm:request_time_per_output_token_seconds	Histogram	Histogram of time_per_output_token_seconds per request.
vllm:time_to_first_token_seconds	Histogram	Histogram of time to first token in seconds.

Speculative Decoding Metrics

Metric Name	Type	Description
vllm:spec_decode_num_accepted_tokens_per_pos	Counter	Accepted tokens per draft position.

NIXL KV Connector Metrics

Metric Name	Type	Description
vllm:nixl_num_failed_notifications	Counter	Number of failed NIXL KV Cache notifications. Retained for compatibility; these failures are also included in vllm:nixl_num_failed_transfers.
vllm:nixl_num_failed_transfers	Counter	Number of failed NIXL KV Cache transfers, including handshake and notification failures. NOTE: KV expiry is tracked separately in vllm:nixl_num_kv_expired_reqs.
vllm:nixl_num_kv_expired_reqs	Counter	Number of requests that had their KV expire. NOTE: This metric is tracked on the P instance.
vllm:nixl_bytes_transferred	Histogram	Histogram of bytes transferred per NIXL KV Cache transfers.
vllm:nixl_num_descriptors	Histogram	Histogram of number of descriptors per NIXL KV Cache transfers.
vllm:nixl_post_time_seconds	Histogram	Histogram of transfer post time for NIXL KV Cache transfers.
vllm:nixl_xfer_time_seconds	Histogram	Histogram of transfer duration for NIXL KV Cache transfers.

Simple CPU Offload Connector Metrics

These metrics are exposed when the SimpleCPUOffloadConnector KV connector is configured (e.g. --kv-transfer-config='{"kv_connector": "SimpleCPUOffloadConnector", "kv_role": "kv_both", "kv_connector_extra_config": {"kv_offload_backend": "disk", "disk_path": "/mnt/nvme/kv"}}'). They are updated once per engine step.

Caveats to keep in mind when interpreting them:

• A "completed" store means the write syscalls returned; it is not fsync-durable, and the disk backend's file is process-lifetime scratch, unlinked at startup and shutdown.
• save_outcomes_total classifies eager-mode boundary hand-off stores; lazy-mode stores are not classified.
• used_blocks counts blocks pinned by in-flight transfers or cache hits; warm cached blocks that are evictable are not counted. Use the capacity_blocks label of simple_kv_offload_info as the denominator.
• Counters and gauges are quantized to engine steps. They are reported by the scheduler process and reflect engine-wide logical block counts, not values pooled from individual tensor-parallel workers.

Metric Name	Type	Description
vllm:simple_kv_offload_load_blocks_total	Counter	KV blocks restored to GPU from the offload pool, counted when a load finishes. This is prefill work avoided through offload cache hits.
vllm:simple_kv_offload_save_outcomes_total	Counter	Store admission decisions in SimpleCPUOffloadConnector, by outcome. Outcomes classify eager-mode boundary hand-off stores; lazy-mode stores are not classified.
vllm:simple_kv_offload_info	Gauge	SimpleCPUOffloadConnector deployment facts. Value is always 1. backend is cpu or disk; page_cache and lazy_offload are true/false; capacity_blocks is the offload pool size.
vllm:simple_kv_offload_pending_store_blocks	Gauge	Offload blocks in pending stores: queued for dispatch, issued to workers, or awaiting release after a cache reset. A persistently growing value indicates a stuck transfer.
vllm:simple_kv_offload_used_blocks	Gauge	Offload-pool blocks currently pinned by in-flight transfers or cache hits (capacity minus free). Evictable cached blocks are not counted; capacity_blocks is on vllm:simple_kv_offload_info.

Model Flops Utilization (MFU) Performance Metrics

These metrics are available via --enable-mfu-metrics:

Metric Name	Type	Description
vllm:estimated_flops_per_gpu_total	Counter	Estimated number of floating point operations per GPU (for Model Flops Utilization calculations).
vllm:estimated_read_bytes_per_gpu_total	Counter	Estimated number of bytes read from memory per GPU (for Model Flops Utilization calculations).
vllm:estimated_write_bytes_per_gpu_total	Counter	Estimated number of bytes written to memory per GPU (for Model Flops Utilization calculations).

Custom Histogram Buckets

The core engine histograms ship with default bucket boundaries tuned for typical serving workloads. The --custom-histogram-buckets option replaces the boundaries of one or more bucket families — exactly the histograms listed in the table below — with your own list; histograms owned by other subsystems (for example, the NIXL connector metrics) are not affected. Use it, for example, to track sub-300ms latency SLOs with the request-phase histograms, whose smallest default boundary is 0.3s:

vllm serve Qwen/Qwen3-0.6B \
    --custom-histogram-buckets '{"request_latency": [0.01, 0.05, 0.1, 0.25, 0.5, 1.0, 5.0, 30.0]}'

Each family key overrides a group of related histograms:

Family key	Histograms
request_latency	vllm:e2e_request_latency_seconds, vllm:request_queue_time_seconds, vllm:request_inference_time_seconds, vllm:request_prefill_time_seconds, vllm:request_decode_time_seconds
time_to_first_token	vllm:time_to_first_token_seconds
inter_token_latency	vllm:inter_token_latency_seconds, vllm:request_time_per_output_token_seconds
iteration_tokens	vllm:iteration_tokens_total
request_params_n	vllm:request_params_n
request_num_preemptions	vllm:request_num_preemptions
request_tokens	vllm:request_prompt_tokens, vllm:request_generation_tokens, vllm:request_max_num_generation_tokens, vllm:request_params_max_tokens, vllm:request_prefill_kv_computed_tokens
kv_cache_residency	vllm:kv_block_lifetime_seconds, vllm:kv_block_idle_before_evict_seconds, vllm:kv_block_reuse_gap_seconds

Bucket values must be positive, finite, and strictly increasing; unknown family keys are rejected at startup. Families you do not list keep their default boundaries. The request_tokens defaults normally scale with --max-model-len; an override replaces that computed list. The kv_cache_residency family only takes effect when --kv-cache-metrics is enabled.

Bucket cardinality

Every bucket boundary creates one extra time series per metric and per label combination (model and engine index, multiplied under data-parallel deployments). Long bucket lists inflate Prometheus storage, scrape sizes, and query costs. Keep custom lists short, and only override the families you actively monitor.

Deprecation Policy

Note: when metrics are deprecated in version X.Y, they are hidden in version X.Y+1 but can be re-enabled using the --show-hidden-metrics-for-version=X.Y escape hatch, and are then removed in version X.Y+2.