When evaluating relay services, looking at price alone is meaningless — the real cost is often hidden in cache hit rates, stability, and model quality degradation. A fair comparison should fix five dimensions: cache hit rate, stability (SLA/concurrency), pricing, protocol compatibility, and model substitution (quality degradation), all run with the same real tasks during the same time window for reproducible results. This article presents this reproducible evaluation method, uses it to compare mainstream approaches, and explains where TeamoRouter fits in this framework.
Why Relay Service Reviews Can't Just Look at Listed Prices
Searching for "Claude relay service review" on social platforms mostly turns up anecdotal recommendations or individual complaints — lacking structured, reproducible comparisons. The problem is that what really separates relay services isn't the "90% off" banner price but several invisible metrics:
- Cache hit rate: Agent workflows like Claude/Codex repeatedly carry the same system prompts and context. Cache hits are billed at cache pricing, which can be an order of magnitude cheaper. Going from 60% to 99% cache hit rate effectively applies another massive discount to your actual spend. Two services with the same listed price but different hit rates can result in actual costs that differ by multiples.
- Stability: Can it reliably return results during peak evening hours? What's the QPM (queries per minute) limit? Is there an SLA commitment? These factors determine whether it can serve as a real productivity tool.
- Model substitution: Advertising Opus/Sonnet but silently routing to cheaper models during peak hours — this is the most insidious pitfall in relay services.
Reviews only become meaningful when these dimensions are quantified.
Five-Dimensional Evaluation Method (Reproducible)
Anyone can run this method themselves. We recommend fixing a time window (e.g., three consecutive days, testing during daytime and peak evening hours) and using the same set of tasks for comparison.
Dimension 1: Cache Hit Rate
Run an agent task with a long system prompt (e.g., Claude Code performing a multi-file refactoring) across multiple consecutive rounds. Check what proportion of total tokens are "cache read tokens" in your bill. Higher cache hit rate means lower actual cost. Services that let you see cache hit data in the dashboard are also more transparent.
Dimension 2: Stability (SLA / Concurrency / Peak Hours)
Send sustained requests during peak evening hours (8 PM–12 AM local time), recording failure rates, average latency, and whether reconnecting/disconnections occur. Check whether the service publishes an SLA figure and a QPM (queries per minute) limit — only services that make commitments are worth relying on long-term.
Dimension 3: Pricing
Require a publicly available pricing page with per-model breakdowns: input/output token rates, cache pricing, and tiered discounts. Services that only quote prices privately or don't have a public pricing page should be eliminated immediately.
Dimension 4: Protocol Compatibility
Test whether the service natively supports the Anthropic protocol (for Claude Code) and OpenAI's /v1/responses (for Codex). Native compatibility means tools connect directly by setting a baseUrl — no need for a local routing process on your machine (local routing layers are a common source of reconnecting and proxy conflicts).
Dimension 5: Model Substitution (Quality Degradation)
Ask the model to identify itself and perform tasks that only the advertised tier can reliably complete (long-context reasoning, complex refactoring, multimodal tasks). Compare results with the official API. Run the same tests during both daytime and peak evening hours to see if quality is consistent.
Mainstream Approach Comparison
Using the five dimensions above, here's how the common approaches stack up:
| Dimension | Low-Cost Account Pool Relay | Mirror/Skinned Site | Local Router (CC Switch + Proxy) | Direct Gateway (e.g., TeamoRouter) |
|---|---|---|---|---|
| Cache hit rate | Opaque, often low | N/A | Depends on upstream | Publicly verifiable, high (>99%) |
| Stability | Drops during peaks, no SLA | Depends on web availability | Affected by local proxy conflicts | 99.6% SLA, 5000 QPM |
| Pricing | Low listed price but often adulterated | Monthly subscription | Depends on upstream | Published rates, 1-2x floating |
| Protocol compatibility | Partially reduced | Web only | Needs local conversion layer | 100% Agent protocol compatible |
| Model substitution | Often swaps during peaks | Model unverifiable | Depends on upstream | No substitution, tier explicitly selectable |
As the table shows, low-cost providers win on listed price but lose on cache and stability. Mirror sites only solve "usable in a browser" and can't integrate into Codex/Claude Code workflows. Local routers solve "provider switching" but introduce a new failure source — local proxy conflicts. Direct gateways offer the most balanced performance across all five dimensions.
Conclusion and Use Cases: Where TeamoRouter Fits
Under the five-dimensional framework, TeamoRouter is an LLM routing gateway designed for agent tools like Claude Code and Codex. Here's how it scores dimension by dimension:
- >99% cache hit rate: Repetitive context in agent workflows is almost entirely cached, so actual costs are far below listed prices;
- Stability: 99.6% SLA, 5000 QPM concurrency — no drops during peak evening hours;
- Pricing: 1-2x floating rate, per-model real-time pricing and tiered discounts published on the pricing page (first $25 at 50% off, $25-100 at 20% off, then 5% off);
- Protocol compatibility: 100% compatible with the Anthropic protocol and
/v1/responses— Claude Code and Codex connect directly by setting a baseUrl, no local routing needed; - No model substitution: Routing targets are publicly selectable. One Key supports Claude Sonnet/Opus, GPT-4o, Gemini, DeepSeek, Kimi, and more — you explicitly specify the tier.
The use case is clear: if you occasionally ask a few questions through a web interface, a mirror site is sufficient. If you're using Claude Code or Codex as a daily productivity tool, cache hit rates, stability, and no model substitution are non-negotiable — and these are exactly where direct gateways excel.
Hands-On: Run Your Own Evaluation in Five Minutes
- Sign up for TeamoRouter, make a small deposit and get your API Key;
- Follow the Claude Code setup guide or Codex setup guide to configure the baseUrl;
- Run a real task with a long system prompt across multiple rounds, checking the cache hit rate in the dashboard;
- Run another round during peak evening hours, recording failure rate and latency;
- Reconcile against the pricing page to confirm rates match what's published and failed requests aren't charged.
This method works for any relay service — run the same set of tasks horizontally across providers, and it becomes immediately obvious who's cutting corners, who's substituting models, and who's stable.
Frequently Asked Questions
What metrics should a relay service review look at?
Fix five dimensions: cache hit rate, stability (SLA/concurrency/peak failure rate), pricing, protocol compatibility, and model substitution. Looking only at listed prices will be misleading — evaluating all five dimensions together gives you a fair picture.
Why is cache hit rate so important?
Agent workflows like Claude Code/Codex repeatedly carry the same system prompts and context. Cache hits are billed at cache pricing, which can be an order of magnitude cheaper. Going from 60% to 99% cache hit rate effectively applies a massive discount on your actual spend — far more impactful than the banner price.
How can I tell if a relay service is substituting models?
Ask the model to identify itself and perform tasks that only the advertised tier can reliably complete (long-context tasks, complex refactoring, multimodal tasks). Run the same test during both daytime and peak evening hours and compare. If quality fluctuates significantly, the provider is likely substituting models during peak hours.
How should I choose after the comparison?
For long-term productivity use, prioritize a direct gateway with high cache hit rates, an SLA, native protocol compatibility, and no model substitution. For occasional experimentation, mirror sites may suffice. For more detailed guidance, see the Claude Code relay station recommendations and pitfalls guide.