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Duplicate
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
model_label: string
url: string
model: string
mode: string
max_tokens: int64
repeats: int64
context_sweep: list<item: struct<context_tier_tokens: int64, sample_prompt_tokens_qwen_flat: int64, concurrency: in (... 515 chars omitted)
  child 0, item: struct<context_tier_tokens: int64, sample_prompt_tokens_qwen_flat: int64, concurrency: int64, ok: in (... 503 chars omitted)
      child 0, context_tier_tokens: int64
      child 1, sample_prompt_tokens_qwen_flat: int64
      child 2, concurrency: int64
      child 3, ok: int64
      child 4, errors: int64
      child 5, error_rate: double
      child 6, total_wall_s: double
      child 7, avg_ttft_s: double
      child 8, sum_decode_tps_all_streams: double
      child 9, aggregate_tokens_per_s: null
      child 10, total_prompt_tokens: int64
      child 11, total_completion_tokens: int64
      child 12, per_request: list<item: struct<ok: bool, wall_s: double, error: string, prompt_tokens: int64, completion_tokens:  (... 96 chars omitted)
          child 0, item: struct<ok: bool, wall_s: double, error: string, prompt_tokens: int64, completion_tokens: int64, ttft (... 84 chars omitted)
              child 0, ok: bool
              child 1, wall_s: double
              child 2, error: string
              child 3, prompt_tokens: int64
              child 4, completion_tokens: int64
              child 5, ttft_s: double
              child 6, decode_tps: double
              child 7, tokens_per_s: null
              child 8, milestone
...
currency_sweep: list<item: struct<concurrency: int64, ok: int64, errors: int64, error_rate: double, total_wall_s: do (... 446 chars omitted)
  child 0, item: struct<concurrency: int64, ok: int64, errors: int64, error_rate: double, total_wall_s: double, avg_t (... 434 chars omitted)
      child 0, concurrency: int64
      child 1, ok: int64
      child 2, errors: int64
      child 3, error_rate: double
      child 4, total_wall_s: double
      child 5, avg_ttft_s: double
      child 6, sum_decode_tps_all_streams: double
      child 7, aggregate_tokens_per_s: null
      child 8, total_prompt_tokens: int64
      child 9, total_completion_tokens: int64
      child 10, per_request: list<item: struct<ok: bool, wall_s: double, error: null, prompt_tokens: int64, completion_tokens: in (... 94 chars omitted)
          child 0, item: struct<ok: bool, wall_s: double, error: null, prompt_tokens: int64, completion_tokens: int64, ttft_s (... 82 chars omitted)
              child 0, ok: bool
              child 1, wall_s: double
              child 2, error: null
              child 3, prompt_tokens: int64
              child 4, completion_tokens: int64
              child 5, ttft_s: double
              child 6, decode_tps: double
              child 7, tokens_per_s: null
              child 8, milestone_s: struct<50: double>
                  child 0, 50: double
      child 11, median_decode_tps: double
      child 12, p50_time_to_50_tokens_s: double
      child 13, mean_decode_tps: double
to
{'model_label': Value('string'), 'url': Value('string'), 'model': Value('string'), 'mode': Value('string'), 'max_tokens': Value('int64'), 'repeats': Value('int64'), 'concurrency_sweep': List({'concurrency': Value('int64'), 'ok': Value('int64'), 'errors': Value('int64'), 'error_rate': Value('float64'), 'total_wall_s': Value('float64'), 'avg_ttft_s': Value('float64'), 'sum_decode_tps_all_streams': Value('float64'), 'aggregate_tokens_per_s': Value('null'), 'total_prompt_tokens': Value('int64'), 'total_completion_tokens': Value('int64'), 'per_request': List({'ok': Value('bool'), 'wall_s': Value('float64'), 'error': Value('null'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'ttft_s': Value('float64'), 'decode_tps': Value('float64'), 'tokens_per_s': Value('null'), 'milestone_s': {'50': Value('float64')}}), 'median_decode_tps': Value('float64'), 'p50_time_to_50_tokens_s': Value('float64'), 'mean_decode_tps': Value('float64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              model_label: string
              url: string
              model: string
              mode: string
              max_tokens: int64
              repeats: int64
              context_sweep: list<item: struct<context_tier_tokens: int64, sample_prompt_tokens_qwen_flat: int64, concurrency: in (... 515 chars omitted)
                child 0, item: struct<context_tier_tokens: int64, sample_prompt_tokens_qwen_flat: int64, concurrency: int64, ok: in (... 503 chars omitted)
                    child 0, context_tier_tokens: int64
                    child 1, sample_prompt_tokens_qwen_flat: int64
                    child 2, concurrency: int64
                    child 3, ok: int64
                    child 4, errors: int64
                    child 5, error_rate: double
                    child 6, total_wall_s: double
                    child 7, avg_ttft_s: double
                    child 8, sum_decode_tps_all_streams: double
                    child 9, aggregate_tokens_per_s: null
                    child 10, total_prompt_tokens: int64
                    child 11, total_completion_tokens: int64
                    child 12, per_request: list<item: struct<ok: bool, wall_s: double, error: string, prompt_tokens: int64, completion_tokens:  (... 96 chars omitted)
                        child 0, item: struct<ok: bool, wall_s: double, error: string, prompt_tokens: int64, completion_tokens: int64, ttft (... 84 chars omitted)
                            child 0, ok: bool
                            child 1, wall_s: double
                            child 2, error: string
                            child 3, prompt_tokens: int64
                            child 4, completion_tokens: int64
                            child 5, ttft_s: double
                            child 6, decode_tps: double
                            child 7, tokens_per_s: null
                            child 8, milestone
              ...
              currency_sweep: list<item: struct<concurrency: int64, ok: int64, errors: int64, error_rate: double, total_wall_s: do (... 446 chars omitted)
                child 0, item: struct<concurrency: int64, ok: int64, errors: int64, error_rate: double, total_wall_s: double, avg_t (... 434 chars omitted)
                    child 0, concurrency: int64
                    child 1, ok: int64
                    child 2, errors: int64
                    child 3, error_rate: double
                    child 4, total_wall_s: double
                    child 5, avg_ttft_s: double
                    child 6, sum_decode_tps_all_streams: double
                    child 7, aggregate_tokens_per_s: null
                    child 8, total_prompt_tokens: int64
                    child 9, total_completion_tokens: int64
                    child 10, per_request: list<item: struct<ok: bool, wall_s: double, error: null, prompt_tokens: int64, completion_tokens: in (... 94 chars omitted)
                        child 0, item: struct<ok: bool, wall_s: double, error: null, prompt_tokens: int64, completion_tokens: int64, ttft_s (... 82 chars omitted)
                            child 0, ok: bool
                            child 1, wall_s: double
                            child 2, error: null
                            child 3, prompt_tokens: int64
                            child 4, completion_tokens: int64
                            child 5, ttft_s: double
                            child 6, decode_tps: double
                            child 7, tokens_per_s: null
                            child 8, milestone_s: struct<50: double>
                                child 0, 50: double
                    child 11, median_decode_tps: double
                    child 12, p50_time_to_50_tokens_s: double
                    child 13, mean_decode_tps: double
              to
              {'model_label': Value('string'), 'url': Value('string'), 'model': Value('string'), 'mode': Value('string'), 'max_tokens': Value('int64'), 'repeats': Value('int64'), 'concurrency_sweep': List({'concurrency': Value('int64'), 'ok': Value('int64'), 'errors': Value('int64'), 'error_rate': Value('float64'), 'total_wall_s': Value('float64'), 'avg_ttft_s': Value('float64'), 'sum_decode_tps_all_streams': Value('float64'), 'aggregate_tokens_per_s': Value('null'), 'total_prompt_tokens': Value('int64'), 'total_completion_tokens': Value('int64'), 'per_request': List({'ok': Value('bool'), 'wall_s': Value('float64'), 'error': Value('null'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'ttft_s': Value('float64'), 'decode_tps': Value('float64'), 'tokens_per_s': Value('null'), 'milestone_s': {'50': Value('float64')}}), 'median_decode_tps': Value('float64'), 'p50_time_to_50_tokens_s': Value('float64'), 'mean_decode_tps': Value('float64')})}
              because column names don't match

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Nanbeige4.2-3B AWQ — gentoo quality / speed / context / concurrency gauntlet

Separate dataset from LostGentoo/gentoo-small-model-throughput-vllm. Same harness (conc + ctx throughput + lighteval chat_core), single model: AWQ W4A16 of Nanbeige4.2-3B on the Nanbeige vLLM fork.

Setup

Setting Value
Host gentoo (3× RTX 5060 Ti 16 GB)
GPU CUDA device 2
Engine Nanbeige/vllm @nanbeige42
Model LostGentoo/Nanbeige4.2-3B-AWQ-W4A16-ASYM
max_model_len 4096
gpu_memory_utilization 0.70
Throughput gen length 128 tokens
Warmup / repeats 2 / 2
Concurrency levels 1, 2, 4, 6, 8, 10, 12, 16, 20
Context tiers 128, 512, 1024, 2048, 4096
Quality suite lighteval chat_core = ifeval, gpqa:diamond, mmlu_pro
Quality concurrent_requests 16
Quality note chat_template thinking default OFF; no --reasoning-parser (answers in content)

Key findings (throughput)

  1. Peak aggregate decode @ conc=20: ~1442 sum-of-stream tok/s (wall agg ~1347 tok/s). Scales smoothly with 0 errors.
  2. Single-stream decode: 87 tok/s @ conc=1 — slower than MiniCPM5-1B (200) / Qwen3.5-0.8B (238) on the same box; closer to Qwen3.5-2B (106).
  3. Context @ conc=10: decode falls from ~78 tok/s/stream @ 128-tier to ~41 @ 2048-tier. 4096 tier n/a (prompt+128 exceeds max_model_len), same pattern as Qwen in the small-model dataset.
  4. Serve caveat: requires Nanbeige vLLM fork + trust_remote_code; stock vLLM cannot load NanbeigeForCausalLM.

Concurrency sweep

conc TTFT (ms) mean decode (tok/s) sum decode (tok/s) wall agg (tok/s) err
1 17.8 87.1 87.1 86.1 0
2 25.0 86.6 173.2 169.3 0
4 34.4 85.2 340.8 330.6 0
6 46.4 84.9 509.1 490.9 0
8 63.1 84.4 675.0 645.5 0
10 67.4 80.4 804.0 767.5 0
12 80.0 80.1 961.2 910.0 0
16 87.8 78.5 1255.5 1179.9 0
20 109.0 72.1 1441.9 1346.6 0

Context sweep

tier conc TTFT (ms) mean decode (tok/s) sum decode (tok/s) wall agg (tok/s) err
128 1 18.4 86.9 86.9 85.9 0
128 10 49.4 78.2 781.8 702.3 0
512 1 19.8 85.0 85.0 80.0 0
512 10 70.3 66.3 663.4 476.9 0
1024 1 22.0 82.5 82.5 73.9 0
1024 10 76.1 54.7 547.2 330.6 0
2048 1 25.5 79.2 79.2 64.7 0
2048 10 108.7 40.8 408.5 200.6 0
4096 1 n/a n/a n/a n/a 1
4096 10 n/a n/a n/a n/a 10

Quality (chat_core)

  • source: quality/LostGentoo_Nanbeige4.2-3B-AWQ-W4A16-ASYM/results/openai/LostGentoo/Nanbeige4.2-3B-AWQ-W4A16-ASYM/results_2026-07-22T12-13-40.991373.json
  • wall seconds: 16886.941249988973
  • max_samples: None
task metric value
`ifeval 0` prompt_level_strict_acc
`ifeval 0` inst_level_strict_acc
`ifeval 0` prompt_level_loose_acc
`ifeval 0` inst_level_loose_acc
`gpqa:diamond 0` gpqa_pass@k:k=1
`mmlu_pro 0` extractive_match

Quality section updated 2026-07-22T12:14:58

Files

Files

File Description
*_scale_conc.json Concurrency sweep
*_scale_ctx.json Context-length sweep
quality/ lighteval chat_core outputs
SUMMARY.md Run log / pass-fail
README.md This card

Generated 2026-07-22T07:43:40

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