AygeaandClaude
2f99dd1e35
7 entries (30→37 total). Muse Glimmer 28B (GGUF) avg 80.7 — the strongest model in the benchmark, 6/7 prompts Minor Logic Flaws: lfu 76 | webhook 81 | automation 89 | rust 85 | data 88 | tts 58 | mcp 88 Standout results: - rust 85 (KAT 36, Qwen3-Coder 54) — real tokio channels (mpsc::channel, not hallucinated mpsc::bounded), two-tier CancellationToken, zero clippy lints; one-line E0507 compile fix. - automation 89 — first model to print a correct summary (98/2/0/100); atomic temp+fsync+rename checkpointing. - data 88 edges out Gemma-26B's 86; mcp 88 sets the bar on a new prompt. Only weak spot: tts 58 (backpressure raises instead of awaits, like Qwen3-Coder). Captured via the native /api/v1/chat fix (real tok/sec + TTFT). Slow deep-thinker: ~17-19 t/s, 5-9 min/prompt, ~5-9k tokens incl. reasoning. Also gitignore checkpoint.json (automation test runtime artifact). Co-Authored-By: Claude <noreply@anthropic.com>
15 lines
379 B
JSON
15 lines
379 B
JSON
{
|
|
"model_instance_id": "meta/muse-glimmer",
|
|
"stats": {
|
|
"input_tokens": 495,
|
|
"total_output_tokens": 4749,
|
|
"reasoning_output_tokens": 3228,
|
|
"tokens_per_second": 20.201965201572563,
|
|
"time_to_first_token_seconds": 2.571259
|
|
},
|
|
"response_id": "resp_a37c5d6bb520db613250881b4919be086d4aed4a8f3a078a",
|
|
"_output_types": [
|
|
"reasoning",
|
|
"message"
|
|
]
|
|
} |