whatmodel.sh · find the best speech-to-text models you can run

Best speech-to-text models for long recordings to run locally on a 16GB Mac

A leaderboard of the best speech-to-text models for long recordings you can run locally on a Mac with 16GB of memory. Whisper large-v3 is #1 right now, followed by Whisper large-v3-turbo and Parakeet TDT 0.6B v2. Models are ranked on transcription tests with long recordings. Each model shows the download that fits and the command to run it.

11 models · scores combine 1 benchmarks · updated how it works · find a leaderboard · benchmark your machine
task[all tasks][long-form transcription][multilingual transcription]

Scores use reviewed long-form transcription evaluations only. Compare scores within this task. Models without task measurements are excluded.

Models for 16GB RAM · Apple Silicon → ~11GB fast · local only · reset
+ more
chip[M1][M1 Pro][M2][M2 Pro][M3][M4][M5][M6 (16GB)]
set[all sets][Open ASR English long-form WER · 31][Voxtral report · English long-form 4-set WER · 4]

Filter the model list while keeping task scores. Models without a shared score scale are not yet calibrated; select a set to see its own scores.

Detect your exact chip or graphics card:

curl -G whatmodel.sh/stt -d max=0 --data-urlencode "mac=$(sysctl -n hw.memsize machdep.cpu.brand_string)"Mac

curl -G whatmodel.sh/stt -d max=0 --data-urlencode "ram=$(awk '/MemT/{print $2}' /proc/meminfo)" --data-urlencode "nv=$(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>/dev/null)"Linux

curl.exe -G whatmodel.sh/stt -d max=0 --data-urlencode "ram=$((gcim Win32_ComputerSystem).TotalPhysicalMemory)" --data-urlencode "nv=$(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>$null)"Windows

$ terminal

detecting your OS…

Run curl "whatmodel.sh/stt?ram=16&gpu=apple&max=0"to get this list in your terminal (add &format=json for agents).

ram[8][16][24][32][48][64][96][128][192][256]GB
gpu[apple silicon][graphics card][none]
price[local][$0.001][$0.002][$0.005][any]max per audio min

detecting your OS…

Score vs memory to run

#modeltask score↓where↓speed↓RAM↓get itsources
#modeltask score↓where↓speed↓RAM↓get itsources
8Whisper large-v3 · fp16 OpenAI58±10*local~4.2GBhow to run › Open ASR Leaderboard
9Whisper large-v3-turbo · fp16 OpenAI58±10*local~2.4GBhow to run › Open ASR Leaderboard
11Parakeet TDT 0.6B v2 · onnx-fp32 NVIDIA56±10*local~3.4GBhow to run › Open ASR Leaderboard
12Parakeet TDT 0.6B v3 · onnx-fp32 NVIDIA55±10*local~3.5GBhow to run › Open ASR Leaderboard
14Whisper large (v1) · fp32 OpenAI54±10*local~7.9GBhow to run › Open ASR Leaderboard
15Whisper large-v2 · fp32 OpenAI54±10*local~7.9GBhow to run › Open ASR Leaderboard
20Distil-Whisper distil-large-v3 · fp16 Hugging Face (Distil-Whisper)51±10*local~2.3GBhow to run › Open ASR Leaderboard
26Distil-Whisper distil-large-v2 · fp16 Hugging Face (Distil-Whisper)30±10*local~2.3GBhow to run › Open ASR Leaderboard
31Distil-Whisper distil-medium.en · fp16 Hugging Face (Distil-Whisper)16±10*local~1.4GBhow to run › Open ASR Leaderboard
—Kyutai STT 2.6B (en) · bf16 Kyutainot yet calibratedlocal~6.7GBhow to run › Voxtral Realtime
—Voxtral Mini 4B Realtime (2602) · 4bit Mistralnot yet calibratedlocal~3.2GBhow to run › Voxtral Realtime

+ 24 more don't fit your machine or budget · show them

35 of 35 catalogue models listed here · sources and licences

* new or thinly tested: ranked on too few benchmark results · † only the maker’s own numbers so far · ~RAM is estimated; full context may need more memory