Local Model Benchmarks

Local test machine: Apple M5 Pro · 64 GB unified memoryRun window 29 September — 18 October 202622 recorded runs

2 October 2026 · Agentic game · 3D baseball

Hardball 3D · Sushi 1.1.0

Session completed Local run

Completed a three-inning 3D arcade baseball game with batting, pitching, fielding, scoring, and restart behavior. The visual presentation is acceptable, but gameplay does not consistently follow baseball rules.

Hardball 3D gameplay at the top of inning one, showing the field, players, scoreboard and ball call
Hardball 3D · gameplay capture

What was checked

  • Final Vite production build completed; the generated JavaScript bundle was reported as 549 KB across 13 modules.
  • Headless autopilot simulation completed three full games, reached game over, and confirmed restart reset the game to ready.
  • Focused runner-on-third scenario recorded the runner scoring at 4.17 simulated seconds.
  • DOM-stub smoke check advanced a game with the real HUD and CameraDirector for 3,600 frames without exceptions.
  • Development server checks returned HTTP 200 for the page, application module, and Three.js.

Limits of this evidence

The initial session used provider ID mlx-sushi and recorded four failed requests with zero token usage. The successful session used provider ID sushi. The matching engine log identifies Sushi 1.1.0 with MLX 0.32.3, EXL3 K=2.625 bpw, and a 131,072-token context. Its 130 response summaries provide the per-request records archived here. Exact server options and output limits were not retained. Request-start-to-first-token latency is not logged; peak system memory was not sampled. The build and recorded smoke checks completed, but those checks do not validate baseball rule fidelity. The original prompt, session transcript, server logs and local paths are excluded from the archive.

Configuration

The model, serving engine and agent used for this execution.

Recorded configuration and setup details
FieldValueDetail
Model · primaryQwen 3.8 Flash Next · primaryEXL3 K=2.625 bpw (provider ID label: 2.6 bpw)
RuntimeSushi 1.1.0 · MLX 0.32.3inference engine and exact build
HarnessPi coding agentthe agent or client that drove the run
HardwareApple M5 Pro · 64 GB unified memoryhardware recorded for this execution
WorkloadHardball 3D · revision 1Interactive three-inning 3D baseball coding challenge; not a fixed task-suite score.
Context window131,072 tokensmaximum context configured for the serving runtime
Repetitions1executions recorded for this workload; one means an indicative result, not an estimate

Inference measurements

Engine-side rates for this run. Each figure states its own statistic; figures from different runs are not interchangeable.

Inference measurements: recorded value and measurement definition
MetricValueDefinition
Decode · per-request median36.6 tok/smedian · n=130
Decode · output-weighted33.9457 tok/stotal output tokens / summed per-request decode time · n=130
Prefill · median413.6 tok/smedian; includes cache reuse · n=130
Prefill · mean407.33 tok/smean; includes cache reuse · n=130
MTP acceptance72.9341 %accepted draft tokens / drafted tokens · n=75571 · 55,117 accepted out of 75,571 drafted tokens across 130 matched requests.

Agent session counters

Agent-wide usage totals. These include reasoning, tool calls and waiting, and are not model decode speed.

Agent session counters: recorded value and measurement definition
MetricValueDefinition
Session elapsed90.6 minfirst logged provider attempt to final response across both Pi sessions · n=1
Successful session elapsed90.0 minsuccessful Sushi session start to final response; includes coding and checks · n=1
Model responses130 responsesassistant responses recorded in the successful Sushi session · n=1
Tool calls133 callstotal in the successful Pi session · n=1
Context compactions2 compactionstotal · n=1
Failed first-session requests4 requestsfailed first-session requests; zero token usage reported and excluded from the successful session totals · n=1
Matched model requests130 requestsone-to-one Pi/Sushi usage match · n=1

Context and token counters

Token totals as reported by the harness or engine. Cached and cumulative figures are not additive with fresh input.

Context and token counters: recorded value and measurement definition
MetricValueDefinition
Fresh input259,165 tokenssum of Pi usage counters · n=1
Cached input8,079,060 tokenssum of Pi cache-read counters · n=1
Output tokens148,981 tokenssum of Pi usage counters · n=1
Request records & provenance

Matched 130 successful Pi assistant responses one-to-one with Sushi runtime summaries using fresh input, cached input and output token counts. The engine records provide per-request prefill/decode rates and MTP accepted/drafted counters. Neither log records request-start-to-first-token latency; Pi event gaps include tool calls and agent work, so TTFT is unavailable.

Run ID: 2026-10-02-qwen38-flash-next-sushi-hardball-3d

One execution, with checks transcribed from the retained record. A completed session is not a quality score. Measurement method · All runs