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[nvbug/5361223] doc: Update Llama4 deployment guide: update config & note concurrency #6222

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merged 4 commits into from
Jul 22, 2025
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[nvbug/5361223] doc: Update Llama4 deployment guide: update config & note concurrency #6222

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5102bcd
Update LLama 4 doc config and note concurrency
raayandhar Jul 21, 2025
74a8beb
remove disable_overlap_scheduler: false
raayandhar Jul 21, 2025
333f796
Merge branch 'main' into Llama4Doc
raayandhar Jul 21, 2025
affb0ed
Merge branch 'main' into Llama4Doc
raayandhar Jul 22, 2025
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6 changes: 4 additions & 2 deletions docs/source/blogs/tech_blog/blog6_Llama4_maverick_eagle_guide.md
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Expand Up @@ -68,7 +68,7 @@ docker run -d --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \
-p 8000:8000 --gpus=all -e "TRTLLM_ENABLE_PDL=1" \
-v /path/to/maverick:/config/models/maverick -v /path/to/eagle:/config/models/eagle \
docker.io/<username>/tensorrt_llm:main sh \
-c "echo -e 'enable_attention_dp: false\nenable_min_latency: true\nenable_autotuner: false\ncuda_graph_config:\n max_batch_size: 8\nspeculative_config:\n decoding_type: Eagle\n max_draft_len: 3\n speculative_model_dir: /config/models/eagle\nkv_cache_config:\n enable_block_reuse: false' > c.yaml && \
-c "echo -e 'enable_autotuner: false\nenable_attention_dp: false\nenable_min_latency: true\ncuda_graph_config:\n max_batch_size: 8\nspeculative_config:\n decoding_type: Eagle\n max_draft_len: 3\n speculative_model_dir: /config/models/eagle\n eagle3_one_model: true\nkv_cache_config:\n enable_block_reuse: false' > c.yaml && \
TRT_LLM_DISABLE_LOAD_WEIGHTS_IN_PARALLEL=True \
trtllm-serve /config/models/maverick \
--host 0.0.0.0 --port 8000 \
Expand Down Expand Up @@ -141,7 +141,9 @@ docker kill <container_id>

## Performance Tuning

The configuration provided is optimized for 8xB200 GPUs, but you can adjust several parameters for your specific workload:
The configuration provided is optimized for 8xB200 GPUs, but you can adjust several parameters for your specific workload.

**Note:** This configuration is optimized for minimum latency (`enable_min_latency: true`). When increasing the concurrency of requests, the tokens per second (TPS) per user degrades rapidly. This setup is designed to maximize single-user performance rather than high-concurrency throughput. For workloads with many concurrent users, you may need to adjust the configuration accordingly.

- `max_batch_size`: Controls how many requests can be batched together
- `max_draft_len`: The number of tokens Eagle can speculate ahead
Expand Down