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QuantFactory

Phi-3.5-mini-instruct-GGUF

Can I run Phi-3.5-mini-instruct-GGUF on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 1 hosted file; check the file list for the exact selection. A file-size fit is an estimate, not a successful run or speed promise. Read the license before use.

Phi-3.5-mini-instruct-GGUF is an open-weights language model for text generation. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.

As of the recorded file availability check on .

Recorded SHA-256 for Phi-3.5-mini-instruct.Q4_K_M.gguf: 3ef532675b6684b28e0a1a0dca8b3bf4132673bf2294b7d87b41b1d64bb03bca. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.

Updated · Page-copy source revision 8871bab84e1cf80aea1686a944ec335078a6c036 · Source files: apps/web/lib/model-page-template.mjs, apps/web/lib/model-page-v3.mjs, apps/web/lib/aeo-page.mjs · Full revision record

Model metadata: As of at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked .

Try browser chat with a small demo model (a separate model; device support is checked before loading).

QuantFactory/Phi-3.5-mini-instruct-GGUF
Model details
text generationLicense: mitSHA-256 recorded for 14 of 16 filesGGUF

Content controls: not assessed.

The catalog lists this model for working with code. Catalog sources: license, cardMetadata.license, tags, task, cardMetadata.pipelineTag.

Proof Lab tested runs

Open a tested command to copy it. Check its paths and settings before running it in your terminal.

Measured on the hardware below. Other machines and answer quality are untested.

Phi-3.5-mini-instruct.Q4_K_M.gguf

llama.cpp server · apple-m4-16gb

· llama.cpp b11630

Answer starts in
0.10 s
Answer speed
37.1 tokens/s
Peak process memory
3.83 GiB

Timed from the request after the server was ready.

Tested command
'/Volumes/Crucial X9/clawd/hb-mac-measurements-20261022/llama-b11630/llama-server' -m results/run-3ef532675b6684b28e0a1a0dca8b3bf4132673bf2294b7d87b41b1d64bb03bca/Phi-3.5-mini-instruct.Q4_K_M.gguf -c 4096 --host 127.0.0.1 --port 18767 -ngl 99 --parallel 1 --cache-ram 0 --reasoning off --verbosity 4 --reasoning-budget 0
curl -sS -N http://127.0.0.1:18767/v1/chat/completions -H 'Content-Type: application/json' -d '{"messages": [{"role": "user", "content": "Explain why the sky is blue in four complete sentences."}], "max_tokens": 128, "temperature": 0, "stream": true, "stream_options": {"include_usage": true}}'

Recorded on the lab host above. Review paths and settings before running.

Signed run evidence

Measurement details

Time to first token (TTFT): request-to-first-content-after-server-ready. Answer speed: runner-eval. Peak memory scope: darwin-time-max-child-high-water-rss-bytes-including-model-load. Memory is shown in gibibytes (GiB).

4096 context tokens. Chat template: passed.

File fingerprint

SHA-256: 3ef532675b6684b28e0a1a0dca8b3bf4132673bf2294b7d87b41b1d64bb03bca

How we measure