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Clash Performance Optimization: Reduce Memory Usage and Boost Speed

2026-08-07 Reading time: ~ 7 min

Table of Contents

Understanding Clash Resource Consumption

Clash is inherently lightweight, but as your configuration grows with hundreds of nodes, thousands of rules, and complex DNS setups, resource consumption scales accordingly. The primary consumers of CPU and memory in Clash are the rule-matching engine, the asynchronous DNS resolver, and the virtual network interface (TUN). When you experience high memory usage or sluggish throughput, the bottleneck usually lies in one of these three areas. By systematically optimizing your configuration, you can significantly reduce the footprint of the proxy daemon without sacrificing functionality.

Optimizing the Proxies Section

Protocol selection and connection multiplexing directly impact CPU cycles and memory allocation. Every active connection holds state in memory, and inefficient multiplexing can lead to socket exhaustion.

Multiplexing Tuning

If you are using protocols like vmess, vless, or trojan, enable smux to reuse TCP connections. However, improper smux settings can cause memory leaks or high CPU usage due to frequent connection rebuilding.

smux:
  enabled: true
  max-connections: 32
  min-streams: 16
  max-streams: 0
  padding: false
  statistic: false

Set max-connections to a reasonable number like 32. Setting it too high wastes memory, while setting it too low causes frequent handshakes. Keep statistic: false unless you are actively debugging, as tracking stream statistics adds overhead.

Minimize TLS Overhead

Modern protocols rely heavily on TLS. Every TLS handshake consumes CPU cycles for cryptographic operations. If your nodes support it, ensure you are using TLS 1.3, which reduces the handshake to one round-trip. Additionally, avoid using client-fingerprint spoofing (like chrome or ios) unless strictly necessary for bypassing DPI. Spoofing requires Clash to generate complex TLS ClientHello extensions, adding marginal CPU overhead per connection.

Tuning DNS Configuration for Speed

DNS resolution is often the hidden culprit behind slow browsing and high CPU usage. Clash's built-in DNS resolver is powerful but can become a bottleneck if misconfigured. For a deep dive into secure DNS setups, refer to our guide on Clash DNS Anti-Pollution.

Switch to Fake-IP Mode

The fake-ip mode eliminates the need for remote DNS resolution for every request by returning a fake IP address immediately. This drastically reduces latency and memory usage associated with DNS caching.

dns:
  enable: true
  listen: 0.0.0.0:1053
  ipv6: false
  enhanced-mode: fake-ip
  fake-ip-range: 198.18.0.1/16
  fake-ip-cache-size: 8192
  fake-ip-filter:
    - '*.lan'
    - localhost.ptlogin2.qq.com
  nameserver:
    - 223.5.5.5
    - 119.29.29.29

Increasing fake-ip-cache-size to 8192 (default is usually lower) ensures that frequently accessed domains are resolved instantly from memory, reducing CPU interrupts.

Streamlining Rules and Rule Providers

Rule evaluation in Clash is strictly sequential. If you have 500 rules, a connection hitting the last rule requires evaluating all 499 preceding rules. For a comprehensive breakdown of rule syntax, see Clash YAML Configuration File Complete Reference.

Rule Ordering Strategy

Always place high-hit-rate rules at the top of your rules list. Local network rules (DOMAIN-SUFFIX,local,DIRECT), followed by direct domains, and finally proxy domains. Put MATCH at the very end.

Optimize Rule Providers

When using rule-providers, choose the most efficient behavior. The classical behavior is the slowest because it evaluates multiple rule types per entry. If a remote rule provider only contains domains, force the behavior to domain.

rule-providers:
  reject:
    type: http
    behavior: domain
    url: 'https://cdn.jsdelivr.net/gh/Loyalsoldier/clash-rules@release/reject.txt'
    path: ./ruleset/reject.yaml
    interval: 86400

Using behavior: domain allows Clash to load the rules into a highly optimized hash map, reducing lookup time from O(N) to O(1).

Managing Proxy Groups and Health Checks

Health checks are essential for failover, but aggressive polling wastes bandwidth and CPU. If you have 100 nodes and set the interval to 10 seconds, Clash is making 10 requests per second constantly.

Avoid Aggressive Polling

Setting interval below 60 seconds for large proxy groups is rarely necessary and will significantly increase memory usage due to concurrent HTTP client allocations.

Configure Efficient Health Checks

Set the interval to 300 seconds (5 minutes) for standard groups, and enable lazy: true. Lazy evaluation stops health checks when the group is not actively selected by any rule.

proxy-groups:
  - name: Proxy
    type: select
    proxies:
      - HK-01
      - US-01
    url: 'http://www.gstatic.com/generate_204'
    interval: 300
    tolerance: 50
    lazy: true

Advanced Tuning: Tun, Script, and Profile

Advanced features like TUN mode and Lua/JavaScript scripting provide immense power but come with a performance cost.

TUN Stack Selection

The stack parameter in TUN mode dictates how packets are processed. system is the fastest and uses the least memory, but requires root/admin privileges and may lack compatibility with some UDP traffic. gvisor is safer but slower. mixed uses system for TCP and gvisor for UDP, offering a good balance.

tun:
  enable: true
  stack: mixed
  dns-hijack:
    - any:53
  auto-route: true
  auto-detect-interface: true

Scripting Overhead

Using script (Lua) or rules with complex regular expressions can severely degrade performance. The script engine must be invoked for every single connection. If you must use scripts, keep the logic extremely simple and avoid heavy string manipulations. Prefer native rules and rule-providers whenever possible, as they are written in highly optimized Go code.

For the profile section, enable store-selected: true to cache your proxy selections across restarts, preventing the need to re-evaluate default proxies immediately. However, disable store-fake-ip: true if you experience memory bloat after long uptimes, as the fake-IP cache can grow indefinitely.

Monitoring and Profiling Clash Performance

Optimization is an iterative process. You cannot improve what you do not measure. Clash exposes a RESTful API that allows you to monitor resource consumption in real-time.

Querying the Clash API

Use curl to fetch memory and traffic statistics. Ensure your external controller is enabled in the config.

curl -H "Authorization: Bearer YOUR_SECRET" http://127.0.0.1:9090/memory
curl -H "Authorization: Bearer YOUR_SECRET" http://127.0.0.1:9090/traffic

Monitor the inuse and oslimit fields in the memory endpoint. If inuse steadily climbs over days, you likely have a memory leak in your rule providers or smux configuration.

Additionally, when evaluating node performance, ensure you are testing the actual throughput and latency rather than just relying on health check URLs. For detailed methodologies, check out our guide on Clash Node Speed Test.

Continuous Optimization

Clash performance optimization is not a one-time setup. As your rule sets grow and node counts increase, periodically review your configuration. Keep your rule providers updated, prune unused proxy groups, and adjust DNS cache sizes based on your network's query volume. A lean configuration ensures maximum throughput and minimal resource drain.

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