01AudioKokoro / community
Kokoro-82M
A compact 82M text-to-speech model suited to local audio pipelines, CPU inference, and lightweight browser prototypes.
USE IT
ENTRY COSTOpen model; deployment costs vary
84/100INDEX SIGNAL
HEAD-TO-HEAD SPECIFICATION & VRAM MATRIX
Kokoro-82M vs ElevenLabs
Side-by-side technical trade-offs across real GGUF quantization VRAM math (24GB target rig), context retention, commercial license terms, and brutal truth verdicts.
COMPARED ENGINES2 / 3
+Add a 3rd engine to this comparison:
01Audio
02AudioElevenLabs
ElevenLabs
A voice AI platform for text-to-speech, voice workflows, and audio production, with a free tier and developer API.
USE IT
ENTRY COSTFree tier; Starter $5/mo
93/100INDEX SIGNAL
SIDE-BY-SIDE TECHNICAL MATRIX
2 engines · 13 criteriaWhere each engine wins: Kokoro-82M vs ElevenLabs
| CRITERION | Kokoro-82MKokoro / community | ElevenLabsElevenLabs |
|---|---|---|
| VERDICT | USE IT | USE IT |
| THE BRUTAL TRUTH | Runs on CPU, tiny footprint, Apache 2.0 — the only reason not to use it is voice quality. If you need premium voices, pay for ElevenLabs. | If you need premium voices, this is the default. Kokoro-82M is 60% of the quality for free — the gap is voice cloning and language coverage. |
| CATEGORY | Audio | Audio |
| ARCHITECTURE & PARAMS | Kokoro-82M | Proprietary voice models |
| QUANTIZATION & MIN VRAM | ONNX CPU: 2GB · FP16 GPU: 4GB | Hosted only |
| RECOMMENDED VRAM | 3 GB (with KV Cache) | Cloud API |
| CONTEXT WINDOW | Text-to-speech | Voice product dependent |
| LICENSE TERMS | Apache 2.0 | Product terms |
| PRICING & ENTRY COST | Free weights · your hardware | Free / $5 mo+ per seat |
| TRUE FOUNDATION ENGINE? | ✓ Foundation Engine | ✓ Foundation Engine |
| STRENGTHS | Very small footprint for a TTS model · Runs on CPU without a discrete GPU | Broad voice production capabilities · Mature API for developers |
| KNOWN GOTCHAS | Language coverage is narrower than commercial TTS · Voice cloning is limited compared with hosted platforms | Commercial usage depends on plan and terms · Voice cloning requires consent safeguards |
| CLOUD GPU DEPLOY | Deploy on RunPod ($0.14/hr) ↗ | Official Website ↗ |
VRAM Precision Footnote: Stactora benchmarks assume typical KV cache overhead at 8K context and modern runtime engines (Ollama, vLLM, ComfyUI). Actual memory usage may vary with longer context or parallel batching.