PRA Runtime Bundle for mlx-community/Qwen3-8B-4bit · MLX / 4bit

What this PRA Runtime Bundle is

This repository packages the model-specific Progressive Retrieval Attention (PRA) structural mapping, runtime profiles, optional learned components, compatibility metadata, and measured qualification evidence. It does not contain the base-model weights and is not an ordinary LoRA quality fine-tune.

  • Base model: mlx-community/Qwen3-8B-4bit
  • Immutable revision: 545dc4251c05440727734bcd94334791f6ab0192
  • Architecture: Qwen3ForCausalLM
  • Parameters: 8B
  • Tokenizer revision: 545dc4251c05440727734bcd94334791f6ab0192
  • Serving precision: INT4 / MLX-4bit
  • Post-training: pretrained and post-trained

Recommended configuration

  • Engine: mlx
  • Recommended PRA mode: Native Memory
  • Recommended profile: BALANCED
  • Bundle evidence tier: ENGINE_QUALIFIED
  • Native Memory status: QUALIFIED

Availability, qualification, and recommendation are separate. A mode may be implemented without being qualified or recommended for this identity.

Precision qualification

Precision evidence is scoped to the exact model conversion, engine, mode, and profile. Qualification does not transfer automatically between BF16, INT8, INT4, or encoding-specific formats.

Family Encoding Serving Feature extraction Adaptor parameters Engine Mode Profile Evidence Datasets
INT4 MLX-4bit INT4 NEEDS_RUN NO_QUALIFIED_ADAPTER mlx Native Memory BALANCED ENGINE_QUALIFIED NOT_MEASURED

Headline results

Workload Selected Context quality Native Memory quality Delta NM vs SC Visible-context delta NM vs SC TTFT delta NM vs SC Completion delta NM vs SC Paired parity Evidence
combined (n=15) token_f1=0.2365 token_f1=0.2365 +0.0000 -89.1% -0.6% +3.0% 15/15 ENGINE_QUALIFIED

All headline rows freeze the PRA-selected evidence. Deltas are Native Memory minus Selected Context; negative latency and visible-context deltas are reductions. These rows contain no ordinary No-PRA arm.

Evidence receipt: mlx-lm 0.31.3; Apple M4 Pro (Mac16,7), 48 GB; selector-frozen natural QA (n=15); 2026-09-01; PRA commit 4b4486a66c80d09aa7982be29812d4027c57a4e3; artifact qualification/qwen3_8b_mlx_profiles.json; SHA-256 43a316c4ecca24420d5d5bc839d2b7a94d9a1074cbe5449092f23a6ba0acf47f.

Evidence by engine, mode, and profile

Each row identifies the exact runtime surface for which metrics are available. MEASURED counts scalar metrics with real observations; missing profile/mode combinations are not inferred from another row.

Engine Mode Profile No PRA Mode / no adaptor Same mode / bundle Measured metric groups
mlx Native Memory QUALITY CALIBRATION_PENDING Native Memory: CALIBRATION_PENDING Native Memory + Bundle: CALIBRATION_PENDING CALIBRATION_PENDING
mlx Native Memory BALANCED NEEDS_RUN Native Memory: MEASURED (16) Native Memory + Bundle: NO_QUALIFIED_ADAPTER context, quality, resources, serving
mlx Native Memory ECONOMY CALIBRATION_PENDING Native Memory: CALIBRATION_PENDING Native Memory + Bundle: CALIBRATION_PENDING CALIBRATION_PENDING

Canonical staged evidence

Each table holds task, hardware, engine, model, precision, and profile fixed. Every delta names its source and target; bundle use is held orthogonal to execution depth.

combined / mlx-lm / balanced

Exact identity: mlx-community/Qwen3-8B-4bit at 545dc4251c05440727734bcd94334791f6ab0192 on Apple M4 Pro (Mac16,7), 48 GB; precision INT4 / MLX-4bit.

Quality

Metric Unit Direction Selected Context Native Memory Native Memory + Bundle Delta NM vs SC Delta Bundle vs NM
Token F1 fraction higher_is_better 0.236455 0.236455 NO_QUALIFIED_ADAPTER +0 (+0.00%) NO_QUALIFIED_ADAPTER
Exact Match fraction higher_is_better 0 0 NO_QUALIFIED_ADAPTER +0 NO_QUALIFIED_ADAPTER
Gold Answer Log Probability log_probability higher_is_better -12.2676 -12.2676 NO_QUALIFIED_ADAPTER +0 (-0.00%) NO_QUALIFIED_ADAPTER

Context

Metric Unit Direction Selected Context Native Memory Native Memory + Bundle Delta NM vs SC Delta Bundle vs NM
Visible Tokens token lower_is_better 315.533 34.2667 NO_QUALIFIED_ADAPTER -281.267 (-89.14%) NO_QUALIFIED_ADAPTER
Selected Native K/V Tokens token neutral 0 10125.6 NO_QUALIFIED_ADAPTER +10125.6 NO_QUALIFIED_ADAPTER

Serving

Metric Unit Direction Selected Context Native Memory Native Memory + Bundle Delta NM vs SC Delta Bundle vs NM
TTFT p50 (ms) ms lower_is_better 115.775 115.061 NO_QUALIFIED_ADAPTER -0.713958 (-0.62%) NO_QUALIFIED_ADAPTER
TTFT p95 (ms) ms lower_is_better 183.02 231.031 NO_QUALIFIED_ADAPTER +48.0105 (+26.23%) NO_QUALIFIED_ADAPTER
TTFT p99 (ms) ms lower_is_better 183.02 231.031 NO_QUALIFIED_ADAPTER +48.0105 (+26.23%) NO_QUALIFIED_ADAPTER
ITL p50 (ms) ms lower_is_better 18.787 19.4877 NO_QUALIFIED_ADAPTER +0.700714 (+3.73%) NO_QUALIFIED_ADAPTER
ITL p95 (ms) ms lower_is_better 18.9825 20.5185 NO_QUALIFIED_ADAPTER +1.53595 (+8.09%) NO_QUALIFIED_ADAPTER
ITL p99 (ms) ms lower_is_better 18.9825 20.5185 NO_QUALIFIED_ADAPTER +1.53595 (+8.09%) NO_QUALIFIED_ADAPTER
Output Tokens Per Second output_token/s higher_is_better 53.3045 51.1062 NO_QUALIFIED_ADAPTER -2.19834 (-4.12%) NO_QUALIFIED_ADAPTER
Completion Latency Mean (ms) ms lower_is_better 275.946 284.088 NO_QUALIFIED_ADAPTER +8.14217 (+2.95%) NO_QUALIFIED_ADAPTER

Resources

Metric Unit Direction Selected Context Native Memory Native Memory + Bundle Delta NM vs SC Delta Bundle vs NM
Active Detail Bytes byte lower_is_better 0 4.14745e+07 NO_QUALIFIED_ADAPTER +4.14745e+07 NO_QUALIFIED_ADAPTER
Retained Detail Bytes byte lower_is_better 0 4.14745e+07 NO_QUALIFIED_ADAPTER +4.14745e+07 NO_QUALIFIED_ADAPTER
Peak Memory Bytes byte lower_is_better 5.18009e+09 5.13407e+09 NO_QUALIFIED_ADAPTER -4.60226e+07 (-0.89%) NO_QUALIFIED_ADAPTER

Installation

pip install 'pra-hf[hf-hub,hf-runtime]'
pra doctor

Quickstart

pra inspect mlx-community/Qwen3-8B-4bit -e mlx -a EInnovator/pra-qwen3-8b-mlx-4bit
pra evaluate mlx-community/Qwen3-8B-4bit -e mlx -D qasper -a EInnovator/pra-qwen3-8b-mlx-4bit
pra recommend .pra/runs/latest
pra serve mlx-community/Qwen3-8B-4bit -e mlx -a EInnovator/pra-qwen3-8b-mlx-4bit -p balanced

Profiles

Profile Purpose Routing Consumer layers Status Recommendation
QUALITY Candidate maximum-quality profile; held-out calibration is incomplete generic cosine all eligible CALIBRATION_PENDING Not promoted
BALANCED Qualified default preserving the all-eligible consumer geometry generic cosine all eligible QUALIFIED Default
ECONOMY Reduced-consumer candidate; the held-out quality gate has not passed generic cosine CALIBRATION_PENDING CALIBRATION_PENDING Not promoted

Engine compatibility

Engine Selected Context Native Memory Native Serving Recommended today
mlx validated QUALIFIED NOT_APPLICABLE Native Memory with BALANCED

End-to-end qualification

Workload Mode Quality Visible tokens TTFT p50 Completion mean Hardware Evidence
2wikimultihopqa (n=5) Selected Context token_f1=0.3578 351.2 114.2 ms 271.9 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
2wikimultihopqa (n=5) Native Memory token_f1=0.3578 31.6 113.8 ms 278.3 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
hotpotqa (n=5) Selected Context token_f1=0.3016 262 180.3 ms 311.6 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
hotpotqa (n=5) Native Memory token_f1=0.3016 43.4 179 ms 325 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
qasper (n=5) Selected Context token_f1=0.05 333.4 114.1 ms 244.4 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
qasper (n=5) Native Memory token_f1=0.05 27.8 112.6 ms 249 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
combined (n=15) Selected Context token_f1=0.2365 315.5 115.8 ms 275.9 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED
combined (n=15) Native Memory token_f1=0.2365 34.27 115.1 ms 284.1 ms Apple M4 Pro (Mac16,7), 48 GB ENGINE_QUALIFIED

Native Memory qualification

Native Memory uses the same selector output as Selected Context. It is recommended only where the profile and engine tables say so.

Workload Selected native K/V tokens Active detail Peak memory Completion cost vs Selected Context
2wikimultihopqa 1.151e+04 44.94 MiB 4.77 GiB 1.023x
hotpotqa 7870 30.74 MiB 4.74 GiB 1.043x
qasper 1.1e+04 42.98 MiB 4.78 GiB 1.019x
combined 1.013e+04 39.55 MiB 4.78 GiB 1.03x

Research diagnostics

No separate routing diagnostic is packaged for this bundle.

These are qualification measurements, not guaranteed production performance. Run pra evaluate on your hardware and workload. Engine version, profile, cohort, evidence tier, date, and artifact provenance remain recorded in qualification/ and bundle.yaml.

How to evaluate locally

pra evaluate mlx-community/Qwen3-8B-4bit -e mlx -a EInnovator/pra-qwen3-8b-mlx-4bit -D qasper -o .pra/runs/qasper
pra recommend .pra/runs/qasper
pra report .pra/runs/qasper --format html

Known limitations

  • No learned router is bundled for this exact quantized identity; routing-adapter transfer from another quantization is intentionally disallowed.
  • Paired natural-QA evidence contains 5 examples per dataset and supports engine qualification, not production qualification.
  • Reduced consumer-layer configurations failed the held-out quality gate; BALANCED therefore retains all eligible layers.
  • The qualification identity is the exact 4bit MLX model and revision; it does not transfer automatically to another checkpoint, engine, or quantization.
  • The selector-frozen natural-QA run qualifies the generic Native Memory path; an exact learned-adaptor arm still requires a separate run.
  • Base-model and dataset licenses apply separately to the router artifact.

Training/creation

The structural adapter is training-free. Learned-component training metadata is stored beside each component and summarized in bundle.yaml.

Reproducibility

  • PRA commit: 81f42d69936bf50eb6fe11a0f7477b415bbf250d
  • Bundle build commit: 81f42d69936bf50eb6fe11a0f7477b415bbf250d
  • Bundle schema: 2
  • PRA package: 0.2.0rc1
  • Component fingerprints and file checksums are recorded in bundle.yaml.

Community/support

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