NVIDIA / NVIDIA/TensorRT-Model-Connect

[Performance] mistral-7b latency is 65.5% above the FP16 reference

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AI bug
Dominant language
Python
Stars
254
Forks
58
Avg merge
1d 7h
Merged PRs (30d)
235

Description

This was generated by AI during triage.

Summary

mistral-7b completes aligned FP16 generation and matches exact token IDs, but TRTMC latency is 65.5% above the reference.

Observed behavior

  • Precision: TRTMC FP16, reference FP16
  • Output contract: exact token IDs (matched)
  • Request: batch 1, 10 new tokens
  • Measurement: 3 warmups followed by 10 iterations
  • Candidate p50: 200.32 ms
  • Reference p50: 121.01 ms
  • Regression: +65.5% (allowed margin: 5%)

Expected behavior

The registered generation case should remain within its performance margin with output parity preserved.

Acceptance criteria

  • Profile prefill, decode, KV-cache handling, and synchronization.
  • Identify and fix the dominant latency source.
  • Preserve exact-token output and the existing performance gate.

Reproduction platform

  • Hardware: NVIDIA Thor X
  • Architecture: aarch64
  • TensorRT: 11.0
  • GPU carveout: 48 GiB

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the registered mistral-7b generation case and its existing performance gate, then profile prefill, decode, KV-cache handling, and synchronization on the stated NVIDIA Thor setup. Identify the dominant latency source, preserve exact token IDs, and confirm the measured latency returns within the 5% margin.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, performance
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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