Slam 1 overview
Slam 1 by Assembly AI
It offers substantial gains in accuracy and adaptability, directly improving transcription workflows in complex real-world environments.
Slam 1 specs
- Model ID
aai/slam-1- Developer
- Assembly AI
- Input
- Audio
- Output
- Text
- Endpoint
POST https://api.aimlapi.com/v1/stt/create
Slam-1 is AssemblyAI's groundbreaking Speech Language Model (SLM) that unifies large language model architecture with advanced automatic speech recognition (ASR) encoders to deliver superior speech-to-text transcription accuracy. Designed specifically for speech tasks, Slam-1 understands context and semantics at a deep level, enabling promptable and customizable transcription that adapts to specialized industry terminology and complex spoken content. This makes Slam-1 ideal for use cases in healthcare, legal, sales, and technical domains requiring precise and context-aware transcription.
Performance Benchmarks
- Reduces missed entity rates by up to 66%, especially for names, medical, and technical terms.
- Decreases formatting errors by approximately 20%.
- Preferred by over 72% of end users in blind tests versus competing models.
- Achieves more reliable transcript quality in noisy and specialized contexts versus previous models.
- Delivers robustness against hallucinations through a multi-modal architecture that simultaneously processes audio and language.
Architecture Breakdown
Slam-1’s architecture distinctively merges a speech encoder with an adapter layer tuned to link acoustic features with a fixed large language model, enabling powerful semantic understanding. This multi-modal design surpasses traditional audio-to-text models by interpreting spoken content holistically, supporting accurate transcription and contextual reasoning. The approach leverages prompt engineering to customize transcription accuracy dynamically for industry-specific vocabularies and speech patterns.
Core Features & Capabilities
- Speech and Language Integration: Combines speech encoder and LLM for promptable and customizable transcription workflows.
- Fine-Tuning & Customization: Enables domain-specific adaptation through simple prompts without retraining.
- High Accuracy: Superior recognition of rare and domain-specific terms, improving downstream analytics and reducing manual review.
- Multi-Channel & Speaker Diarization: Supports complex audio streams with speaker separation and timestamps out of the box.
- Enterprise Ready: Designed to reduce post-processing effort and improve transcript quality in high-stakes industries like healthcare and legal.
Comparison with Other Models
VS AssemblyAI Universal: Slam-1 offers promptable, highly customizable transcription with superior entity recognition for specialized domains, while AssemblyAI Universal provides broader language support and lower latency for general transcription needs.
VS GPT-4.1 (audio transcription use): Slam-1 is specifically optimized for speech-to-text with multi-channel and speaker diarization features, unlike GPT-4.1, which focuses on general NLP tasks without native audio processing capabilities.
Use cases
- Medical scribing with enhanced capture of prescription names, diagnoses, and medical terminology.
- Legal transcription with improved accuracy for case citations, legal phrases, and procedural terms.
- Sales and contact center call analysis benefiting from better recognition of product names and company details.
- AI-powered meeting notes and content analytics with reduced error rates and formatting issues.
How to use the Slam 1 API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/stt/create' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "aai/slam-1"
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "aai/slam-1"
}
response = requests.post("https://api.aimlapi.com/v1/stt/create", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/stt/create", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "aai/slam-1"
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());The request returns a generation id. Poll GET https://api.aimlapi.com/v1/stt/create?generation_id=<id> until the status is completed.
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Slam 1 FAQ
What inputs and outputs does Slam 1 support?
Slam 1 takes audio as input and returns text.
How much does Slam 1 cost?
Slam 1 is priced at output $0.0000975 / sec.
Who created Slam 1?
Slam 1 was built by Assembly AI.
How do I call Slam 1 on AI/ML API?
Send a request to v1/stt/create with aai/slam-1 as the model id.
Is Slam 1 available through a single API key?
Yes. Slam 1 is served through AI/ML API, so the same key and endpoint format used for other models applies.
What is the Slam 1 model ID?
Use aai/slam-1 as the model parameter. Requests go to https://api.aimlapi.com/v1/stt/create with your AI/ML API key.