“Alternative to OpenRouter” can mean four very different things: a cheaper gateway, a self-hosted proxy, a set of direct provider accounts, or simply staying put. This page compares those four options on the parts that affect an engineering team — migration effort, pricing, routing, and who owns the operational burden.
Written 2026-10-26. Prices and model counts are snapshots; the comparison logic is what should last.
What changed, and why teams are looking
OpenRouter's recent ownership change is the usual trigger: teams want to know whether pricing, routing, and data-handling terms will stay the same. The honest answer is that nobody outside the company can promise that. The useful response is to reduce the number of assumptions your stack makes about any single gateway.
That is what the four options below do in different ways. One keeps a managed gateway but changes the vendor. One keeps your provider accounts and puts a proxy you own in front. One removes the gateway entirely. One accepts the marketplace and its risks.
The four options at a glance
| Option | What it is | Best for | Main trade-off |
|---|---|---|---|
| JZS Token | Managed OpenAI-compatible gateway with a curated catalog and one USD price per model. | Teams that want a smaller surface, predictable per-token pricing, and a single prepaid balance. | Fewer models, no batch tier, no self-hosting. |
| LiteLLM | Open-source proxy you run yourself; bring your own provider keys. | Teams that already have provider accounts and want routing/fallback under their own control. | You own uptime, upgrades, rate limits, and billing reconciliation. |
| Direct provider APIs | Call OpenAI, Anthropic, Google, DeepSeek, and Qwen directly. | Teams with one or two primary providers that need first-party features and support. | Multiple keys, SDKs, invoices, and per-provider quotas. |
| OpenRouter | Marketplace gateway across many providers, with free and batch routes. | Products that need the long tail, free models, or per-request provider preferences. | Another intermediary, route-dependent pricing, and the change you were reacting to. |
1. JZS Token
JZS is a managed gateway with a deliberately shorter catalog. It speaks the OpenAI API, supports the standard chat, responses, and messages endpoints, and publishes one USD price per model. You buy prepaid credit, create a key, and change the base URL. There is no subscription and no per-request marketplace deciding which upstream serves you.
Pros: predictable list prices; one balance across models; a catalog small enough that support can answer questions about it; WhatsApp and email support; no monthly minimum. The pricing is especially aggressive on Claude, GPT, Qwen, and Gemini — see the table below.
Cons: 69 models instead of 467; no batch tier; no free inference; no self-hosted option; support runs on UTC+8 hours. If a model is not in the catalog, it is not a quiet fallback — it is a 403 model_not_supported.
2. LiteLLM
LiteLLM is the option for teams that want to keep their own provider accounts and put a router they control in front of them. It is open source, runs next to your application, and handles provider normalization, fallbacks, and budget controls. If your security team will not approve another hosted intermediary, this is the cleanest answer.
Pros: full control of routing and keys; no new vendor in the data path; can run inside your VPC; useful when you already have committed spend with multiple providers.
Cons: you own the operational surface — upgrades, Redis or Postgres for budgets, latency, provider outages, and the reconciliation between multiple invoices. The engineering cost is real and recurring, especially for a small team.
3. Direct provider APIs
If you use one or two providers, the simplest architecture is no gateway at all. OpenAI, Anthropic, Google, DeepSeek, and Qwen all expose their own APIs; you get first-party features, first-party support, and no intermediary. The cost is fragmentation: multiple SDKs and auth schemes, multiple dashboards, multiple rate limits, and no single balance.
Pros: best feature access; clearest data terms; no gateway markup; direct provider support.
Cons: every new model is a new integration; you manage quotas and retries yourself; procurement and invoicing multiply. For a product that switches models often, this becomes a second job.
4. Staying on OpenRouter
This is a legitimate option. OpenRouter has the largest catalog, free endpoints, batch routes, and provider preferences. If your product depends on any of those, moving away can cost more than it saves. The question is whether you are comfortable with the current pricing and routing terms, and whether you can put a fallback in place if they change.
Pros: breadth, free models, batch pricing, provider choice, and an ecosystem that already integrates with many tools.
Cons: you are still exposed to a single intermediary; prices and routes can vary by model and provider; the ownership change is exactly the kind of event that makes teams want a second path.
Price snapshot: JZS vs OpenRouter
The table uses five current models both platforms list, standard non-batch prices, and a 3:1 input/output blend. It is not a complete catalog comparison; it is a like-for-like check on the models most teams actually run.
| Model | OpenRouter in / out | JZS in / out | 3:1 blended (OR → JZS) | JZS saves |
|---|---|---|---|---|
| GPT-5.5gpt-5.5 | $5.00 / $30.00 | $0.39 / $2.34 | $11.250 → $0.876 | 92.2% |
| Claude Sonnet 5.5claude-sonnet-5.5 | $2.00 / $10.00 | $0.78 / $3.89 | $4.000 → $1.557 | 61.1% |
| DeepSeek V4 Prodeepseek-v4-pro | $0.96 / $1.91 | $0.45 / $2.25 | $1.194 → $0.898 | 24.8% |
| Qwen3.7 Maxqwen3.7-max | $1.48 / $4.42 | $0.78 / $2.34 | $2.213 → $1.168 | 47.2% |
| Gemini 4 Argongemini-4-argon | $2.00 / $10.00 | $0.39 / $1.95 | $4.000 → $0.778 | 80.5% |
USD per 1M tokens, standard (non-batch) routes, captured 2026-10-26. Blended assumes 3 input tokens per output token. OpenRouter batch routes are often half price and are not compared here.
Sources: JZS public pricing API and OpenRouter public model list, both read on 2026-10-26. Prices move; check both pages before you commit to a provider.
The pattern is consistent across all five models at the captured standard rates. That is a snapshot, not a law: OpenRouter's batch routes and free endpoints can still be cheaper for specific jobs, and a provider price change can flip any row. Compare the exact model ID and your real token ratio before switching.
What to evaluate (beyond the price table)
The cheapest per-token rate is not the cheapest architecture. Four costs matter, and they show up at different times:
- Integration cost. How many lines change? For an OpenAI-compatible client, JZS and OpenRouter are both a base URL. Direct APIs need a client per provider. LiteLLM needs a service to deploy, monitor, and upgrade.
- Ongoing operations. Who pages when a provider has an outage? With LiteLLM, that is your team. With a managed gateway, it is the gateway's team. With direct APIs, it is each provider's status page and your retry logic.
- Exit cost. How hard is it to leave in six months? Base URL plus model IDs is a low exit cost. A custom proxy with provider-specific config is a higher one. Prefer the option whose exit is a config change.
- Coverage risk. A 69-model catalog is smaller by design. If your product lets users type arbitrary model IDs, that is a product regression. If your team uses five models, it is a feature.
| Option | Setup effort | Ongoing effort | Main hidden cost |
|---|---|---|---|
| JZS Token | Low — base URL + key | Low — managed | Smaller catalog; no batch/free |
| LiteLLM | Medium — deploy a proxy | High — own uptime and upgrades | Engineering time |
| Direct APIs | Medium — one client per provider | Medium — quotas and retries | Fragmented billing |
| OpenRouter | Low — already integrated | Low — managed | Route/pricing and ownership risk |
Common mistakes when switching gateways
- Switching on price alone. Run one real workload for a week. Latency, error rates, and model quality can wipe out a 20% per-token saving.
- Keeping vendor-prefixed model IDs. The most common 403 after migration. Strip the prefix and use the exact catalog ID.
- Cutting over 100% at once. Put the new gateway behind an environment variable and send a small slice first. Rollback should be one flag, not a deploy.
- Assuming every feature is portable. Chat, streaming, and ordinary tools usually are; batch endpoints, free variants, and provider-specific routing are not. Inventory the features your app actually calls.
How to run a two-week evaluation
Do not decide from a comparison page, including this one. Run the same workload through two options for two weeks and compare the things that affect the product:
- The same model ID and prompt version. If the model changes between arms, you are measuring the model, not the gateway.
- Cost per successful request. Token price is an input; retries, truncated responses, and longer outputs change the output. Divide total spend by completed requests.
- p95 latency from your region. Averages hide the tail that users feel. Measure from the same region and at the same concurrency.
- Failure modes. A 429 at the wrong time is a product incident. Check what the gateway does when an upstream provider is slow or unavailable.
Two weeks is enough for a stable workload and short enough that prices do not move much. Keep the comparison in a spreadsheet with the request count, token mix, and error codes; a vague impression of “it felt faster” is not a migration decision.
How to choose without overthinking it
- One or two providers, stable stack: direct APIs are the least machinery. Take the extra invoices.
- Multiple providers, strict data path, in-house ops: LiteLLM. You will pay for it in engineering time, but you own the path.
- Many models, free endpoints, batch jobs: OpenRouter remains the strongest fit. Do not switch just because of a headline.
- A short catalog, one rate, prepaid billing: JZS. The trade-off is breadth; the gain is fewer surprises per request.
If you do switch, switch cheaply
Do not rewrite your application. Put the base URL and model IDs in environment variables, run both gateways behind a feature flag, and compare real requests for a week. Every serious option here speaks the OpenAI API at some level; the migration cost should be configuration, not a refactor.
OPENAI_BASE_URL=https://openrouter.ai/api/v1 # old OPENAI_BASE_URL=https://jzstoken.com/api/v1 # new MODEL=claude-sonnet-5.5 # JZS ID, no vendor prefix
The step-by-step version, including the model-ID mapping and the errors people hit first, is in the migration guide. If price is the main reason you are here, the cost breakdown has the 100M-token math.
FAQ
Is JZS always cheaper than OpenRouter?
No. The five-model table shows a consistent gap at standard non-batch rates, but OpenRouter's batch routes and free endpoints can be cheaper for specific jobs, and model prices change. Compare the exact ID and your real token mix.
Do I need to move all traffic at once?
No, and you should not. Keep both gateways behind an environment variable, send a small slice to the new one, and compare error rates and latency. The cutover is a flag, not a rewrite.
Can I use LiteLLM with JZS?
LiteLLM can front any OpenAI-compatible endpoint, so it is technically possible, but it adds the operational cost LiteLLM exists to solve. If you want JZS plus self-hosted routing, evaluate whether the extra proxy earns its keep.
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The catalog is public. Check the model IDs and per-1M prices before you change anything in production.
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