Rankings data by OpenRouter is licensed under CC BY 4.0. Reuse and republish it with attribution. The Data API docs cover the citation format and JSON access to these datasets.
Rankings data by OpenRouter is licensed under CC BY 4.0. Reuse and republish it with attribution. The Data API docs cover the citation format and JSON access to these datasets.
Live LLM rankings by real-world usage. Models are ranked by tokens processed through the OpenRouter API by millions of developers. View all text models
Usage data through
Weekly usage of models across OpenRouter
Each task’s leading models, ranked by share of spend on OpenRouter
What one coding-agent session typically costs (paid usage), by session length

Each model is ranked by the number of tokens it processed through the OpenRouter API, counting both prompt and completion tokens. Usage is aggregated into daily buckets in UTC and totalled per model variant, so variants of the same model, such as a free variant, are ranked separately. Requests that a user or app keeps private are excluded before aggregation.
Today, This Week, and This Month each cover a trailing window of one day, seven days, and thirty days, ending with the most recent complete daily bucket. Trending compares the trailing seven days with the seven days before it and ranks models by the percentage change in tokens, including only models with at least one million tokens in the current window so that a small base cannot produce a large percentage. New models with no prior week are listed first, up to five of them.
The date above the rankings is the newest usage bucket the leaderboard is computed from, not the time the page was rendered or deployed, so it advances only when new usage data is aggregated.
These rankings show traffic routed through OpenRouter. They do not include usage on a model provider's own API or across the whole market. Token volume is not a count of requests, users, or spend. Models differ in verbosity and tokenization, so a higher token total does not tell you which model is best for a task. They do not rank models by accuracy, reasoning ability, or benchmark performance. The Benchmarks section of this page reports those separately. The Top Models chart groups models outside the top ten as Others. The Market Share chart shows each model author's share of text requests on OpenRouter, with the remaining authors grouped as Others.
Rankings data by OpenRouter is licensed under CC BY 4.0. Reuse and republish it with attribution. The Data API docs cover the citation format and JSON access to these datasets.
| Rank | Model | tokens processed |
|---|---|---|
| 1. | 19T tokens 69% | |
| 2. | 18.4T tokens 79% | |
| 3. | 13T tokens 9% | |
| 4. | 8.74T tokens 50% | |
| 5. | 8.49T tokens 24% |
| Rank | Model | tokens processed |
|---|---|---|
| 6. | 5.66T tokens 28% | |
| 7. | 5.02T tokens 44% | |
| 8. | 3.91T tokens 13% | |
| 9. | 3.46T tokens 18% | |
| 10. | 3.05T tokens 24% |
Text summary of the Today tab of the leaderboard above. Models are ranked by tokens processed on OpenRouter over the most recent complete day, with the change measured against the day before it.
| Rank | Model | Author | Tokens | Change |
|---|---|---|---|---|
| 1 | DeepSeek V4.1 Flash | deepseek | 2.81T | +3% |
| 2 | GLM 5.3 Flash | z-ai | 2.41T | -24% |
| 3 | Hy4 preview | tencent | 1.63T | -22% |
| 4 | GPT-5.6 Luna | openai | 1.24T | -15% |
| 5 | DeepSeek V4 Flash 0731 | deepseek | 1.2T | -3% |
| 6 | MiMo-V2.6-Flash | xiaomi | 567B | +283% |
| 7 | DeepSeek V4 Flash 0423 | deepseek | 515B | -2% |
| 8 | Nemotron 3 Ultra (free) | nvidia | 483B | -36% |
| 9 | Hy3 | tencent | 456B | -5% |
| 10 | GLM 5.3 | z-ai | 451B | +35% |
Text summary of the This Month tab of the leaderboard above. Models are ranked by tokens processed on OpenRouter over the trailing thirty days, with the change measured against the thirty days before them.
| Rank | Model | Author | Tokens | Change |
|---|---|---|---|---|
| 1 | GLM 5.3 Flash | z-ai | 54.4T | new |
| 2 | Hy4 preview | tencent | 52.7T | new |
| 3 | GPT-5.6 Luna | openai | 52T | +202% |
| 4 | DeepSeek V4 Flash 0731 | deepseek | 47.6T | +38% |
| 5 | DeepSeek V4.1 Flash | deepseek | 28.7T | new |
| 6 | MiMo-V2.5 | xiaomi | 26.7T | -6% |
| 7 | Hy3 | tencent | 19.6T | -40% |
| 8 | DeepSeek V4 Flash 0423 | deepseek | 19.3T | -24% |
| 9 | Nemotron 3 Ultra (free) | nvidia | 18.1T | +39% |
| 10 | GLM 5.3 | z-ai | 11T | >999% |
Text summary of the New & Trending tab of the leaderboard above. Models are ranked by the percentage change in tokens processed over the trailing seven days against the seven days before, among models with at least one million tokens in the current week. A model with no prior week is marked new.
| Rank | Model | Author | Tokens | Change |
|---|---|---|---|---|
| 1 | Jev 1.13 | typesafe | 1.39T | new |
| 2 | DeepSeek V4 Flash 0731 (free) | deepseek | 1.09T | new |
| 3 | MiMo-V2.6-Flash | xiaomi | 719B | new |
| 4 | GPT-6 Luna | openai | 482B | new |
| 5 | MiMo-V2.6-Pro | xiaomi | 369B | new |
| 6 | Ministral 3 8B 2512 (batch) | mistralai | 839M | >999% |
| 7 | GPT-5.6 Terra Pro (batch) | openai | 8.32M | >999% |
| 8 | multi-qa-mpnet-base-dot-v1 | sentence-transformers | 32.3M | >999% |
| 9 | Nex-N2.5-Mini | nex-agi | 139M | >999% |
| 10 | Gemini 3.1 Flash Lite (batch) | 5.87B | >999% |
Text summary of the Market Share chart above. Share of text requests made on OpenRouter in the week beginning Sep 14, 2026, with the change in each author's requests against the week before it. deepseek leads at 25.4% of the week's requests. Authors the chart groups as others are listed last, so the rows match the series the chart plots.
| Rank | Author | Share of requests | Change in requests |
|---|---|---|---|
| 1 | deepseek | 25.4% | +9% |
| 2 | 18.6% | -3% | |
| 3 | openai | 17.0% | -30% |
| 4 | z-ai | 9.4% | +31% |
| 5 | qwen | 6.7% | +25% |
| 6 | tencent | 6.4% | -14% |
| 7 | anthropic | 2.7% | +3% |
| 8 | mistralai | 2.6% | +11% |
| 9 | xiaomi | 1.9% | |
| All other authors | 9.3% | +3% |