{ "artifacts": [ { "file": "model.litertlm", "sha256": "2e56093d920bba2b53967d180f1bbf8fbe107710439950055b07a0146f15d887", "size_mb": 2539.528 } ], "benchmarks": [], "conversion": { "command": "from litert_torch.generative.export_hf.export import export; export(model='microsoft/FastContext-1.0-4B-SFT', output_dir='out', quantization_recipe='qwen3_int4_block32_octav.json' | 'qwen3_int4_block128_octav.json', cache_length=4096, externalize_embedder=True) (HF card Conversion snippet)", "quantization": "int4 blockwise (block 32) + OCTAV, symmetric; INT8 embedding externalized; KV cache 4096 (HF card)", "tool": "litert-torch export_hf (official converter; FastContext is a standard Qwen3ForCausalLM, existing Qwen3 path, no custom graph code) (HF card Conversion)", "tool_version": "TODO (the HF card names the converter but not its version; no export log in the sources)" }, "cross_runtime": [], "delegation": null, "device": { "records": [ { "device": "galaxy-s26", "run": { "accelerator": "cpu", "context_length": null, "date": "2026-09-05", "decode_tokens_per_s": 7.14, "delegated_ops": 2448, "env": { "device": "Galaxy S26 (SM-S942Q)", "machine_label": "galaxy-s26-cold-cache-cooled", "os_build": "Android 16", "runtime": "litert-lm", "runtime_version": "0.16.0", "soc": "Qualcomm SM8850", "vendor_sdk": null }, "error": null, "evidence": [ "VERBOSE: Replacing 1454 out of 1674 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 285 partitions for subgraph 0 (prefill_128).", "VERBOSE: Replacing 1374 out of 1596 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 290 partitions for subgraph 1 (decode).", "VERBOSE: Replacing 7 out of 7 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 1 partitions for subgraph 2 (odml.rms_norm.impl).", "VERBOSE: Replacing 7 out of 7 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 1 partitions for subgraph 3 (odml.rms_norm.impl_0).", "results block: prefill=36.95 decode=7.14 tokens/s" ], "failure_class": null, "full_delegation": false, "latency_p50_ms": null, "loads": true, "max_abs_diff": null, "max_rel_diff": null, "metrics": { "decode_tokens": 388.0, "init_s": 4.39303, "prefill_tokens": 202.0 }, "output_match": null, "peak_mem_mb": null, "prefill_tokens_per_s": 36.95, "provenance": "measured", "runs": true, "total_ops": 2526, "ttft_ms": 5610.0 }, "source": "data/device_runs/0.16.0/2026-09-05/fastcontext-4b__galaxy-s26.json" }, { "device": "mac-studio-m4-max", "run": { "accelerator": "gpu", "context_length": null, "date": "2026-07-23", "decode_tokens_per_s": 74.53, "delegated_ops": null, "env": { "device": "Mac Studio (M4 Max)", "machine_label": "mac-studio-m4-max", "os_build": null, "runtime": "litert-lm", "runtime_version": "0.14.0", "soc": "Apple M4 Max", "vendor_sdk": null }, "error": null, "evidence": [ "results block: prefill=963.57 decode=74.53 tokens/s, init=3.2651 s" ], "failure_class": null, "full_delegation": null, "latency_p50_ms": null, "loads": true, "max_abs_diff": null, "max_rel_diff": null, "metrics": { "decode_tokens": 256.0, "init_s": 3.2651, "max_num_tokens": 1024.0, "prefill_tokens": 256.0 }, "output_match": null, "peak_mem_mb": null, "prefill_tokens_per_s": 963.57, "provenance": "measured", "runs": true, "total_ops": null, "ttft_ms": 279.1 }, "source": "data/device_runs/0.14.0/2026-07-23/fastcontext-4b__mac-studio-m4-max.json" }, { "device": "raspberry-pi-5", "run": { "accelerator": "cpu", "context_length": null, "date": "2026-09-02", "decode_tokens_per_s": 1.44, "delegated_ops": null, "env": { "device": "Raspberry Pi 5 Model B Rev 1.1", "machine_label": "raspberry-pi-5-cooled-52c", "os_build": "Linux-6.18.34+rpt-rpi-2712-aarch64-with-glibc2.41", "runtime": "litert-lm", "runtime_version": "0.16.1", "soc": "Broadcom BCM2712", "vendor_sdk": null }, "error": null, "evidence": [ "pi5 LLM sweep row: `litert-lm benchmark --backend cpu --cpu-thread-count 4 -p 256 -d 256 --runs 1 --cache memory` (wave-2 driver pi5_llm_bench.py; --cache memory rather than the house --cache no, which OOM-kills every >=1.2B file on the 8 GB Pi — equivalence measured on granite-350m int8, +2-3%), 3 invocations per file with cool-down to <=52 C between them, vcgencmd measure_temp + get_throttled logged per invocation, peak RSS polled from /proc; throughput = median of the three invocations (spread in metrics); a row counts as measured only when the real-generation gate (`litert-lm run`, degenerate-output check) passed and every invocation exited 0 with get_throttled 0x0", "versions: cpu=Raspberry Pi 5 Model B Rev 1.1, litert-lm=0.16.1, litert-lm-api=0.16.1, platform=Linux-6.18.34+rpt-rpi-2712-aarch64-with-glibc2.41, python=3.13.5", "cache mode 'memory'; -p 256 -d 256 --runs 1 --cpu-thread-count 4", "gate ('What is 17 plus 26? Answer with the number only.'): status pass, exit 0, wall 82.0 s, output head '43'", "invocation 0: exit=0 wall_s=532.3 temp 48.8->52.1C throttled=0x0 prefill_tps=10.21 decode_tps=1.44 ttft_s=28.6196 init_s=63.9159 peak_rss_mb=4404", "invocation 1: exit=0 wall_s=524.4 temp 49.9->52.1C throttled=0x0 prefill_tps=10.24 decode_tps=1.44 ttft_s=28.4606 init_s=63.2913 peak_rss_mb=4372", "invocation 2: exit=0 wall_s=524.4 temp 49.4->56.0C throttled=0x0 prefill_tps=10.23 decode_tps=1.44 ttft_s=28.378 init_s=63.3653 peak_rss_mb=4372" ], "failure_class": null, "full_delegation": null, "latency_p50_ms": null, "loads": true, "max_abs_diff": null, "max_rel_diff": null, "metrics": { "decode_tokens": 256.0, "decode_tps_max": 1.44, "decode_tps_min": 1.44, "init_s": 63.3653, "init_s_max": 63.9159, "init_s_min": 63.2913, "invocations": 3.0, "prefill_tokens": 256.0, "prefill_tps_max": 10.24, "prefill_tps_min": 10.21, "runs_per_invocation": 1.0, "threads": 4.0, "ttft_s_max": 28.6196, "ttft_s_min": 28.378 }, "output_match": null, "peak_mem_mb": 4404.0, "prefill_tokens_per_s": 10.23, "provenance": "measured", "runs": true, "total_ops": null, "ttft_ms": 28460.6 }, "source": "data/device_runs/0.16.1/2026-09-02/fastcontext-4b__raspberry-pi-5.json" } ] }, "model": { "family": "qwen3", "id": "fastcontext-4b", "license": "mit", "source_url": "https://huggingface.co/litert-community/FastContext-1.0-4B-SFT", "task": "text-generation" }, "pitfalls": [ "Which file: block 32 (model.litertlm) is the quality pick — GSM8K 88.0% vs 81.0% for block 128 — while block 128 (model_block128.litertlm) decodes ~40% faster on the iPhone 17 Pro (14 vs 10 tok/s; Mac M-series GPU 66-68 vs 64-73 tok/s) (HF card 'Which file?').", "Blockwise (not the tool's default channelwise) int4 is what preserves accuracy; embeddings kept at INT8 and externalized into their own section (dedups the tied matrix) (HF card Conversion).", "License MIT, inherited from microsoft/FastContext-1.0-4B-SFT (itself built on Qwen3-4B-Instruct) (HF card License).", "LiteRT-LM .litertlm bundle: LiteRT.js cannot run it, so delegation stays null and there is no browser block; device rows come from data/device_runs/ (Pi 5 / S26 / Pixel 8a / Mac / iPhone as measured)." ], "schema_version": "1.2" }