LLM Inference Benchmark Explorer
Qwen3.5-35B-A3B on RTX PRO 6000 — FP8, vLLM, TP1 inference benchmark
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| Model | Qwen3.5-35B-A3B |
|---|---|
| Parameters | 35B |
| Intelligence Index | 19.3 |
| Agentic Index | — |
| Device | RTX PRO 6000 |
| Quantization | FP8 |
| Max C | 64+ |
| Chat Capacity | 150 |
| Agentic Capacity | 55 |
| TP | — |
| DP | — |
| PP | — |
| Engine | vLLM |
| Speculative Decoding | — |
| C | TTFT (ms) | TPS (tok/s) | Status |
|---|---|---|---|
| 1 | 47 | 113.82 | PASS |
| 2 | 61 | 98.56 | PASS |
| 4 | 73 | 83.29 | PASS |
| 8 | 765 | 57.94 | PASS |
| 16 | 136 | 46.98 | PASS |
| 32 | 207 | 32.91 | PASS |
| 64 | 311 | 24.05 | PASS |
In OpenZeka's measurement, Qwen3.5-35B-A3B (35B parameters), served in FP8 format with vLLM on RTX PRO 6000, reached a generation speed of 113.8 tok/s per request and a time to first token (TTFT) of 47 ms with a single request.
Considering the speed targets and the available KV cache capacity, the estimated capacity is 150 users for chat use and 55 for agentic use. The realistic capacity will likely fall between these two values. In scenarios dominated by coding, tool use, long workflows and multi-agent use, capacity approaches the agentic estimate; where shorter interactions, standard conversations and lighter tasks dominate, it approaches the chat estimate.
Intelligence Index and Agentic Index values are published by Artificial Analysis and are reproduced here with attribution.
In OpenZeka's measurement, Qwen3.5-35B-A3B (35B parameters), served in FP8 format with vLLM on RTX PRO 6000, reached a generation speed of 113.8 tok/s per request and a time to first token (TTFT) of 47 ms with a single request.
Considering the speed targets and the available KV cache capacity, the estimated capacity is 150 users for chat use and 55 for agentic use. The realistic capacity will likely fall between these two values. In scenarios dominated by coding, tool use, long workflows and multi-agent use, capacity approaches the agentic estimate; where shorter interactions, standard conversations and lighter tasks dominate, it approaches the chat estimate.