Ollama Cloud vs OpenRouter for speed
They are not the same kind of thing, which is why a single speed number for both does not exist. Ollama Cloud hosts open-weight models directly. OpenRouter is an aggregator that forwards your request to a third-party provider it selects — so its speed for a given model is the speed of whichever upstream served you, plus routing overhead, and it can differ between two identical requests. We measure Ollama Cloud continuously: across 26 models the median sits near 104.4 tokens/s, with GPT-OSS 120B the fastest at 282.7 tokens/s over the last 24 hours. We do not benchmark OpenRouter, so we will not print a number for it.
That limitation is the point of this page. Most comparisons you will find quote both sides from marketing copy. We would rather give you one measured side, one structural explanation, and an honest account of when each choice wins.
What is the actual difference between Ollama Cloud and OpenRouter?
Ollama Cloud is a first-party host: Ollama runs the models on its own infrastructure, and a request goes to that infrastructure directly. OpenRouter is a routing layer: it holds no GPUs of its own and forwards your request to one of many upstream providers, chosen by price, availability and your routing preferences.
The practical consequence for speed is that OpenRouter's throughput for a model is a property of the provider it routed to, not of OpenRouter. Two identical requests can land on different upstreams running different hardware and different quantisations of the same weights, and return materially different tokens-per-second. Benchmarking it meaningfully means benchmarking every upstream it might select, which is a different project from this one.
How fast is Ollama Cloud, measured?
Every figure below is our own measurement, sampled continuously and averaged over the last 24 hours. See how we measure for the exact request shape.
| Model | Plan | Avg tokens/s (24h) |
|---|---|---|
| GPT-OSS 120B | Free | 282.7 |
| GPT-OSS 120B | Pro | 230.3 |
| DeepSeek V4 Flash 0731 | Pro | 174.2 |
| Nemotron 3 Nano 30B | Pro | 156.2 |
| Nemotron 3 Nano 30B | Free | 152.9 |
| Gemma4 31B | Pro | 140.4 |
| Kimi K2.7 Code | Pro | 137.0 |
| DeepSeek V4 Pro 0813 | Pro | 132.3 |
Live figures from the Ollama Cloud leaderboard, which carries every model we track rather than this excerpt.
When is OpenRouter the better choice?
Genuinely often, and it would be dishonest to write this page without saying so:
- Model breadth. OpenRouter reaches closed models — GPT, Claude, Gemini — that Ollama Cloud does not host at all. If you need one of those, there is no comparison to make.
- Failover. One provider going down is OpenRouter's problem to route around, not yours. A direct host has no such fallback.
- One key, one bill. Access to many vendors without holding an account with each.
- Pay-as-you-go. Per-token billing beats a subscription when your usage is low or spiky.
When is Ollama Cloud the better choice?
- Predictable cost at volume. A flat subscription rather than per-token billing, so heavy usage does not scale the bill linearly.
- No routing variable. You know which host served the request, so performance is reproducible and regressions are attributable.
- Local-to-cloud parity. The same models you run locally, reachable with the same API and no code change.
- Open weights. If your requirement is open-weight models specifically, this is a host built around them.
Which should you pick for speed?
If your model is available on Ollama Cloud and you care about consistent, attributable throughput, direct hosting removes a variable that an aggregator cannot remove — and you can check our live numbers before committing. If you need a model Ollama Cloud does not host, or you want automatic failover across vendors, OpenRouter is solving a problem Ollama Cloud does not attempt to solve, and speed is the wrong axis to decide on.
For a cross-provider view that also covers OpenCode Zen and OpenCode Go, see our sister leaderboard TokenDyno.
Frequently asked questions
Is Ollama Cloud faster than OpenRouter?
It depends on the model and the route, and anyone quoting a single number for both is guessing. Ollama Cloud hosts models directly, so a request reaches the inference server over one hop. OpenRouter is an aggregator: it forwards your request to a third-party provider it selects, so its speed for a given model is the speed of whichever upstream served you, plus routing overhead. That makes OpenRouter speed provider-dependent and variable between identical requests. We publish continuous first-party measurements for Ollama Cloud and do not benchmark OpenRouter, so we will not quote a tokens-per-second figure for it.
Do you benchmark OpenRouter?
No. Ollama TPS benchmarks Ollama Cloud directly, and its sister site TokenDyno covers Ollama Cloud plus OpenCode Zen and OpenCode Go. Neither measures OpenRouter. Every number on this page is our own measurement of Ollama Cloud; the OpenRouter side of the comparison is architectural, not numeric.
When is OpenRouter the better choice?
When you want breadth and failover rather than one host. OpenRouter gives a single API key and one billing relationship across many vendors, automatic fallback when a provider is down, and access to closed models such as GPT, Claude and Gemini that Ollama Cloud does not host at all. If you need a model Ollama Cloud does not serve, the speed comparison is moot.
When is Ollama Cloud the better choice?
When you are running open-weight models and want predictable cost and a direct path to the host. Ollama Cloud is a flat subscription rather than per-token billing, so heavy usage does not scale your bill linearly, and requests are not routed through a third party that can change underneath you. It also runs the same models you can run locally, so moving between local and cloud needs no code change.
Why does routing through an aggregator affect speed?
Two reasons. First, the request makes an extra network hop before it reaches any GPU, which adds to time-to-first-token. Second, and much more significant, an aggregator picks among upstream providers that run different hardware and different quantisations of the same model, so the tokens-per-second you get depends on which one served that request. Direct hosting removes the routing variable; it does not by itself guarantee a faster server.