LLM Inference Benchmark Explorer
Qwen3.5-397B-A17B on 4× DGX Spark — INT4, vLLM, TP4 inference benchmark
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| Model | Qwen3.5-397B-A17B |
|---|---|
| Parameters | 397B |
| Intelligence Index | 21.4 |
| Agentic Index | — |
| Device | 4× DGX Spark |
| Quantization | INT4 |
| Max C | 4 |
| Chat Capacity | 16 |
| Agentic Capacity | 6 |
| TP | 4 |
| DP | — |
| PP | — |
| Engine | vLLM |
| Speculative Decoding | — |
| C | TTFT (ms) | TPS (tok/s) | Status |
|---|---|---|---|
| 1 | 325 | 38.14 | PASS |
| 2 | 393 | 30.54 | PASS |
| 4 | 541 | 24.54 | PASS |
| 8 | 622 | 18.83 | FAIL |
In OpenZeka's measurement, Qwen3.5-397B-A17B (397B parameters), served in INT4 format with vLLM on 4× DGX Spark (TP=4), reached a generation speed of 38.1 tok/s per request and a time to first token (TTFT) of 325 ms with a single request.
Considering the speed targets and the available KV cache capacity, the estimated capacity is 16 users for chat use and 6 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.
Notes: Switch topology, TP=4. 2.24x faster than PP=3 at C1.
Intelligence Index and Agentic Index values are published by Artificial Analysis and are reproduced here with attribution.
In OpenZeka's measurement, Qwen3.5-397B-A17B (397B parameters), served in INT4 format with vLLM on 4× DGX Spark (TP=4), reached a generation speed of 38.1 tok/s per request and a time to first token (TTFT) of 325 ms with a single request.
Considering the speed targets and the available KV cache capacity, the estimated capacity is 16 users for chat use and 6 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.