Chinese open-weight labs have captured the majority of token volume on OpenRouter — but a single Western lab still captures the majority of the dollars. The gap between those two facts is the whole investment thesis.
| vendor | vol | Δ% | share | Δpp |
| deepseek | 272.2T | +75% | 38.3% | +10.8pp |
| z-ai | 81.7T | +8% | 11.5% | -1.9pp |
| openai | 68.0T | -10% | 9.6% | -3.8pp |
| anthropic | 59.5T | +127% | 8.4% | +3.7pp |
| tencent | 56.5T | +3% | 8.0% | -1.8pp |
| stepfun | 35.0T | +894% | 4.9% | +4.3pp |
| xiaomi | 32.0T | -26% | 4.5% | -3.2pp |
| 24.8T | -6% | 3.5% | -1.2pp |
| vendor | $ | Δ% | share | Δpp |
| anthropic | $12.6M | -1% | 51.9% | -2.9pp |
| deepseek | $2.5M | +37% | 10.5% | +2.5pp |
| openai | $2.4M | -1% | 10.0% | -0.5pp |
| $1.8M | +1% | 7.6% | -0.2pp | |
| xiaomi | $1.3M | -9% | 5.3% | -0.8pp |
| minimax | $799.9K | +305% | 3.3% | +2.5pp |
| z-ai | $727.9K | -13% | 3.0% | -0.6pp |
| qwen | $629.2K | +2% | 2.6% | -0.1pp |
Δpp = percentage-point shift in share of the total — the zero-sum view of who's taking ground.
The clearest evidence that volume migration threatens revenue: the highest-volume apps run both Anthropic and DeepSeek for the same job. 9 of the top 10 apps mix them — and DeepSeek V4 Flash undercuts Claude Sonnet by ~41× on output price. When a workflow already calls both, switching share is a config change, not a migration cost.
| app | Anthropic | DeepSeek | mix |
| Hermes Agent | 6% | 51% | both |
| Claude Code | 46% | 26% | both |
| Kilo Code | 1% | 8% | both |
| pi | 7% | 62% | both |
| OpenClaw | 1% | 21% | both |
| Codex | 2% | 21% | both |
| Cline | 3% | 1% | both |
| Portkey AI | 0% | 11% | |
| OpenHands | 1% | 74% | both |
| ISEKAI ZERO | 2% | 22% | both |
Share of the app's tokens by vendor. Even Anthropic's own Claude Code routes ~13% to DeepSeek; roleplay/agent apps lean majority-DeepSeek. The cheaper model is already inside the funnel.
Individual versions churn constantly, which makes per-model churn misleading. The real unit is the family: usage migrates within a family (e.g. Claude Opus 4.6 → 4.7 → 4.8) while the family's total tells you whether the franchise is winning. "Lead version" share is a stickiness signal — how fast users consolidate onto the newest release.
| family | recent | Δ% | lead version (stickiness) | migration |
| DeepSeek DeepSeek Flash (batch | 252.5T | +95% | DeepSeek V4.1 Flash 56% | vV4 0731→vV4.1 1017 |
| Z.ai GLM Flash (batch) | 57.1T | +3% | GLM 5.3 Flash (batch 100% | — |
| Tencent Hy4 | 44.0T | +5% | Hy4 preview 71% | v—→v— |
| OpenAI GPT Luna (batch) | 43.9T | -14% | GPT-6 Luna (batch) 75% | v5.6→v6 |
| StepFun Step | 34.2T | +961% | Step 5 Preview 100% | — |
| Anthropic Claude Opus (batch) | 32.3T | +150% | Claude Opus 5.5 (bat 91% | v5→v5.5 |
| Xiaomi MiMo Flash | 24.4T | +4% | MiMo-V2.6-Flash 100% | — |
| Z.ai GLM (batch) | 23.4T | +22% | GLM 5.3 (batch) 83% | v5.2→v5.3 |
| nvidia/nemotron ultra 550b a55 | 19.0T | -15% | nvidia/nemotron-3-ul 100% | — |
| typesafe/jev | 18.8T | +118% | typesafe/jev-1.13-20 70% | — |
| OpenAI GPT Sol (batch) | 16.0T | +32% | GPT-6.1 Sol (batch) 82% | v5.6→v6.1 |
| Anthropic Claude Sonnet (batch | 14.9T | +56% | Claude Sonnet 5.5 (b 73% | v5→v5.5 |
Every tracked model placed on its curve — launch → ramp → peak → decline → death:
A long "declining" tail is normal — it's last-generation versions bleeding into their successors. "Dead" = had real volume, now ~zero with no in-family heir absorbing it.
Models don't age gracefully; they get cannibalised by their own successors. Measuring each generation's useful life (launch → usage falling below half its peak) exposes how fast the treadmill runs — and it runs much faster in the East. Average useful life: China ~63 days vs West ~87 days.
| generation | peak share | useful life | origin |
| Deepseek 3.1 | 5.9% | 10d | China |
| Qwen 2.5 | 13.0% | 11d | China |
| Deepseek 2.5 | 5.8% | 14d | China |
| Deepseek 3 | 9.4% | 18d | China |
| Google 3.7 | 3.5% | 22d | West |
| Minimax 2.5 | 26.2% | 26d | China |
| Google 3.5 | 1.8% | 28d | West |
| Google 3.6 | 3.6% | 30d | West |
| Minimax 2 | 4.5% | 38d | China |
| Google 3.8 | 2.1% | 44d | West |
| Anthropic 4.7 | 9.2% | 46d | West |
| Minimax 3 | 10.7% | 49d | China |
Shortest-lived first. The fastest Chinese generations turn over in under two weeks, while Western flagships hold for two to four months — the table shows the full spread. On average a Chinese generation's useful life is ~63d vs ~87d in the West. Faster churn = faster iteration, but a brutal amortisation window on training spend.