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Description

This PR updates the Disaggregated Serving README to document how to run context and generation servers in mixed-precision using model opt. An example usage for BF16 prefill + FP8 decode is included.

Test Coverage

Performance and accuracy tests were run for FP8 and NVFP4 with llama 3.1 8B base model on GSM8k and MMLU, with 1 Ctx/Gen Server. Example:

FP16/16 (2xH100):
"results": { "gsm8k": { "alias": "gsm8k", "exact_match,strict-match": 0.7558756633813495, "exact_match_stderr,strict-match": 0.011832404674077592, "exact_match,flexible-extract": 0.7839272175890827, "exact_match_stderr,flexible-extract": 0.011336531489638858 } },

"start_time": 34733.35253426, "end_time": 35711.569743744, "total_evaluation_time_seconds": "978.2172094840062"

FP16/8 (2xH100):
"results": { "gsm8k": { "alias": "gsm8k", "exact_match,strict-match": 0.7354056103108415, "exact_match_stderr,strict-match": 0.012150554001563231, "exact_match,flexible-extract": 0.7626990144048522, "exact_match_stderr,flexible-extract": 0.011718409178739442 } },
"start_time": 33387.524966359, "end_time": 34123.906708314, "total_evaluation_time_seconds": "736.3817419550032"

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Added section on mixed precision context and generation, including prerequisites and example commands for setting up context and generation servers with different precisions.

Signed-off-by: Timothy Gao <[email protected]>
Clarify mixed precision serving benefits in README.

Signed-off-by: Timothy Gao <[email protected]>
Expanded explanation on mixed precision context and generation in disaggregated serving.

Signed-off-by: Timothy Gao <[email protected]>
Clarify performance characteristics of prefill and decode workers in mixed precision context.

Signed-off-by: Timothy Gao <[email protected]>

## Mixed Precision Context and Generation

In disaggregated serving, the context (prefill) workers and generation (decode) workers have different performance characteristics: prefill workers are more compute-bound while decode workers are more memory-bound. Therefore, it may be beneficial to run prefill workers in higher precision. Running these workers with different precisions also enables the ability to interpolate between performance/compute trade-offs of different quantization levels.
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No need to specify prefill/decode, the terms are not used in the rest of the document.

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Changed!


## Mixed Precision Context and Generation

In disaggregated serving, the context (prefill) workers and generation (decode) workers have different performance characteristics: prefill workers are more compute-bound while decode workers are more memory-bound. Therefore, it may be beneficial to run prefill workers in higher precision. Running these workers with different precisions also enables the ability to interpolate between performance/compute trade-offs of different quantization levels.
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prefill workers are more compute-bound while decode workers are more memory-bound.

Use context / generation as well here. Remove 'more'

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Changed!

@juney-nvidia juney-nvidia added Community want to contribute PRs initiated from Community Community Engagement help/insights needed from community labels Oct 7, 2025
Signed-off-by: Timothy Gao <[email protected]>
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