TLDR
- Inworld TTS leads public benchmarks for real-time voice, and the top-ranked Inworld TTS-1 model has now been upgraded with TTS-1.5.
- Real-time voice AI now delivers high-quality synthesis without speed/cost tradeoffs
There are three main levers when evaluating text-to-speech (TTS) models: quality of voice generation, cost, and speed. It’s rare for a model to excel at all three domains, but with our latest model at Inworld, we’ve achieved benchmarking-topping quality, scale-friendly pricing, and real-time speed.
Voice is having a catalyzing moment in 2026 with a Cambrian explosion of use-cases. What used to be confined to aftermarket gaming mods and call centers is becoming a key modality of communicating with software. Price has decreased dramatically with our newest models being 25x cheaper than competitive models. While price has decreased, speed and quality have improved dramatically.
If you’re evaluating what text-to-speech model to use for your product in 2026, this guide will help you evaluate leading providers on latency, quality, and cost using performance benchmarks from the Artificial Analysis Speech Leaderboard and the HuggingFace TTS Arena.
Top picks by use-case
Best overall real-time: Inworld TTS-1.5-Max - #1 quality (ELO 1,160)*, sub-250ms latency, $10/1M chars
Fastest time-to-first-audio: Cartesia Sonic 3 - 40ms TTFA, State Space Model architecture
Most languages/voice library: ElevenLabs v3 (70+ languages, 380+ voices) / Google Cloud Studio (75+ languages, 380+ voices)
Best hyperscaler reliability: Amazon Polly (AWS integration, speech marks) / Azure Neural (Microsoft ecosystem)
Cheapest managed: Inworld TTS-1.5-Mini ($5/1M chars) / Hume Octave 2 ($7.60/1M chars)
Best open-weight: Kokoro 82M - ELO 1,059, $0.70/1M chars
*Inworld TTS-1.5 is now live. Public benchmark rankings cited in this article reflect TTS-1-Max, the model currently evaluated on third-party leaderboards. Internal evaluations show TTS-1.5-Max improves on TTS-1-Max across latency, quality, and stability.
What Is a TTS API?
Cloud services convert written text into spoken audio via HTTP or WebSocket requests. Developers send text strings; the API returns audio streams or files.
Neural models synthesize speech through learned voice representations. Streaming endpoints enable real-time playback as audio generates. WebSocket connections support bidirectional communication for conversational AI, while SSML markup controls pronunciation, pitch, speed, and emotion tags.
TTS API Rankings: Complete Leaderboard
Rankings based on
Artificial Analysis Speech Arena Leaderboard using blind user preference tests. Users compare generated speech side-by-side without knowing which models created them. ELO rating system measures quality based on win rates across thousands of comparisons.
Note: Benchmarks and pricing reflect data available as of January 2026 and may change. Latency metrics combine vendor-reported specifications with third-party testing where available. Price-performance calculations use publicly listed API pricing.
Key Findings
Inworld TTS-1.5-Max* holds #1 position with ELO 1,160 based on 2,376 blind comparison votes. That's 52 ELO points ahead of ElevenLabs Multilingual v2 (#7), 55 points ahead of OpenAI TTS-1 (#9), and 107 points ahead of Cartesia Sonic 3 (#20).
Price-performance analysis reveals the gap: Inworld delivers 116 ELO per dollar (1,160 ELO ÷ $10). OpenAI TTS-1 achieves 73.7 ELO per dollar (1,105 ELO ÷ $15). MiniMax Speech 2.6 HD manages 11.5 ELO per dollar (1,154 ELO ÷ $100), while ElevenLabs Multilingual v2 reaches 5.4 ELO per dollar (1,108 ELO ÷ $206).
Inworld delivers 10x better price-performance than the nearest quality competitor and 21.5x better than ElevenLabs.
Inworld AI TTS
Best for: Real-time conversational AI requiring #1 quality at sub-250ms latency without premium pricing.
Inworld TTS ranks #1 on independent benchmarks from
Artificial Analysis, with an ELO of 1,160. P90 time-to-first-audio latency ranges 130-250ms, depending on model choice. Inworld’s TTS costs $5-10 per million characters, which is more than 25x cheaper than alternatives like ElevenLabs Multilingual v3 or ElevenLabs v3.
In
internal evaluation, Inworld TTS-1-Max achieved win rates of 59.1% against ElevenLabs, 60.9% against Cartesia, and 60.7% against OpenAI TTS-1-HD in blind tests.
Models
Inworld TTS is available in two model variants optimized for different use-cases.
TTS-1.5-Max: recommended for most applications. It delivers P90 time-to-first-audio latency under 250ms. Pricing is $10 per million characters, or approximately $0.01 per minute of generated audio. This model offers the optimal balance of quality and latency for all use-cases.
TTS-1.5-Mini: optimized for extremely latency-sensitive applications. It delivers P90 time-to-first-audio latency under 130ms. Pricing is $5 per million characters, or approximately $0.005 per minute of generated audio. This model is suited for applications where response speed is the primary requirement.
Features
Voice cloning: offers both instant cloning from 2-15 seconds of audio (available via API) and professional voice cloning for custom enterprise requirements. Cloned voices maintain stability and realism across extended outputs.
Multilingual: supports 15 languages, including English, Spanish, French, Korean, Dutch, Chinese, German, Italian, Japanese, Polish, Portuguese, Russian, Hindi, Arabic, and Hebrew, with more coming soon.
Other features: support for audio markups such as [happy], [sad], [whisper], non-verbals such as [cough], [sigh], [breathe], word, character, phoneme and viseme-level timestamps, and custom pronunciation.
Deployment options: cloud API with global availability, on-premise deployment for full data sovereignty, EU and India data residency options, and custom solutions/model weights access for enterprises with specific compliance requirements.
Enterprise features: fully enterprise-ready, with full compliance for SOC2 Type II, GDPR, HIPAA (including BAAs) and zero retention mode.
Inworld also open-sourced its full training framework, including everything from codec to SpeechLM fine-tuning. Streaming-native architecture eliminates batch processing bottlenecks while quantization-aware training maintains quality at reduced compute costs.
Pricing
- Inworld TTS-1.5-Mini: $5 per 1 million characters ($0.005 per minute)
- Inworld TTS-1.5-Max: $10 per 1 million characters ($0.01 per minute)
- Zero-shot voice cloning: free for all users
- Professional voice cloning: available upon request
- On-premise deployment: custom enterprise pricing available
Pros
- #1 Quality rankings: Highest ELO score (1,160) on independent benchmarks proves consistent quality leadership through blind preference tests
- Sub-250ms latency: Enables natural conversation turn-taking without perceptible delay, critical for real-time voice agents and interactive applications
- Cost efficiency: Bible Chat case study demonstrates scaling to millions of users at approximately 5% of competitor costs
- Developer SDKs: Unity, Unreal, and Node.js SDKs with lipsync templates, word-level timestamp alignment, and 48 kHz output
- Free voice cloning: Zero-shot cloning from 2-15 seconds of audio with no per-clone licensing fees
- Open research: Full training framework open-sourced, allowing developers to validate claims through reproducible benchmarks
Cons
- Smaller language coverage: 15 languages supported versus competitors offering 70+ languages, restricting options for niche accents and global markets
- Experimental features: Audio markup features (emotion tags) and crosslingual (using the same voice across multiple languages) currently experimental and only fully supported in English per documentation
- Newer market entrant: TTS product launched June 2025, making it relatively new compared to established providers with longer production track records
MiniMax Speech 2.6 HD
Best for: Teams prioritizing quality closest to Inworld but willing to pay 10x more.
MiniMax Speech 2.6 HD ranks #2 on
Artificial Analysis with ELO 1,156, just 7 points below Inworld. Released October 2025 with 4,261 comparison samples, the model represents the closest quality competitor to Inworld TTS-1.5-Max.
Pricing
$100 per 1M characters makes it 10x more expensive than Inworld. Price-performance ratio of 11.6 ELO per dollar (1,156 ELO ÷ $100) trails Inworld's 116.3 by a factor of 10.
Pros
- Near-Top Quality: Second-highest ELO score demonstrates strong voice synthesis capabilities
Cons
- Premium Pricing: 10x more expensive than Inworld for marginally lower quality (7 ELO points difference)
- Limited Information: Relatively new entrant with less public documentation on features and integration
ElevenLabs Multilingual v2
Best for: Content production requiring maximum emotional range across 70+ languages.
ElevenLabs ranks #3 on
Artificial Analysis (ELO 1,108) with 380+ voices across 70+ languages.
Flash v2.5 model delivers 75ms inference latency with extensive emotional range.
According to
independent testing, the platform achieved 81.97% pronunciation accuracy versus OpenAI's 77.30% with 150ms TTFA (90th percentile) faster than OpenAI's 200ms. Hallucination rate sits at 5% versus OpenAI's 10%, making it reliable for accuracy-critical applications.
Pricing
Per
ElevenLabs pricing, Multilingual v2 costs $206 per 1M characters (20.6x more expensive than Inworld). Free tier offers 20,000 characters/month for non-commercial use. Business tier provides 13,750 Conversational AI minutes at $0.08/min with volume discounts available.
Pros
- Extensive Voice Library: 380+ voices across 70+ languages with ability to create custom voices through cloning, design, or remixing
- Superior Pronunciation: 81.97% accuracy versus OpenAI's 77.30% with lower hallucination rates (5% vs 10%)
Cons
- Premium Pricing: $206/1M chars makes it 20.6x more expensive than Inworld for equivalent volume
- Not Full Conversational Stack: Must be paired with separate ASR/LLM for conversations, unlike integrated solutions
OpenAI TTS-1
Best for: Teams already using OpenAI ecosystem seeking integrated TTS.
OpenAI TTS-1 ranks #4 on
Artificial Analysis (ELO 1,106), 57 points below Inworld. Released November 2023 with 7,324 comparison samples, the service integrates with ChatGPT and Realtime API.
Pricing at $15 per 1M characters (1.5x Inworld's price) delivers second-best price-performance ratio (73.7 ELO per dollar) after Inworld (116.3).
Pros
- Ecosystem Integration: Seamless integration with ChatGPT, Realtime API, and OpenAI platform for unified development experience
Cons
- Lower Quality: Ranks 57 ELO points below Inworld despite costing 1.5x more per million characters
StepFun Step TTS 2
Best for: Early adopters willing to test newer models before public pricing launches.
StepFun Step TTS 2 ranks #5 on
Artificial Analysis with ELO 1,090, placing it 73 points below Inworld. Released December 2025 with 786 comparison samples, the model represents one of the newer entrants to the leaderboard.
Pricing
Pricing not yet publicly available. Contact StepFun for enterprise pricing details.
Pros
- Strong Quality: Top 5 ranking demonstrates competitive voice synthesis capabilities
Cons
- Limited Track Record: Only 786 comparison samples versus thousands for established competitors
- No Public Pricing: Lack of transparent pricing makes cost evaluation difficult
async AsyncFlow V2
Best for: Teams seeking mid-tier quality with pricing details forthcoming.
async AsyncFlow V2 ranks #6 on
Artificial Analysis with ELO 1,081, placing it 82 points below Inworld. Released July 2025 with 5,055 comparison samples, the model shows solid adoption in blind testing.
Pricing
Pricing not yet publicly available. Contact async for commercial licensing details.
Pros
- Solid Sample Size: 5,055 comparison votes indicate meaningful user testing and validation
Cons
- Mid-Tier Quality: Ranks 82 ELO points below Inworld
- Limited Public Information: Minimal documentation on features, latency, or integration options
Fish Audio OpenAudio S1
Best for: Developers seeking OpenAI-equivalent pricing with slightly lower quality.
Fish Audio OpenAudio S1 ranks #7 on
Artificial Analysis with ELO 1,074, placing it 89 points below Inworld. Released June 2025 with 5,568 comparison samples, the model offers competitive pricing at $15 per 1M characters.
Pricing
$15 per 1M characters matches OpenAI TTS-1 pricing (1.5x Inworld's cost). Price-performance ratio of 71.6 ELO per dollar (1,074 ELO ÷ $15) trails Inworld's 116.3.
Pros
- Competitive Pricing: Matches OpenAI pricing tier while offering alternative voice options
Cons
- Lower Quality: Ranks 89 ELO points below Inworld at same price point as OpenAI
Amazon Polly Generative
Best for: AWS ecosystem teams needing reliable TTS with speech marks for animation synchronization.
Amazon Polly Generative ranks #8 on
Artificial Analysis (ELO 1,060), 103 points below Inworld. The service offers 100+ voices across 40+ languages with
speech marks enabling word/viseme-level synchronization for animation.
Native AWS integration with Lex, Connect, Chime SDK, and CloudWatch monitoring provides enterprise infrastructure. Cache and replay generated speech at no additional cost per
AWS documentation.
Pricing
Per
AWS Polly pricing, Generative voices cost $30 per 1M characters (3x Inworld's price). Standard voices start at $4 per 1M chars with 5M free first year. Neural voices run $16 per 1M chars with 1M free first year.
Pros
- Speech Marks: Provides viseme data for lipsync and timing information for animation synchronization
- AWS Integration: Native integration with Amazon Lex, Connect, and other AWS services reduces infrastructure complexity
Cons
- Higher Latency: Third-party testing shows 100ms-1 second latency range versus Inworld's sub-200ms consistency
- Limited Expressiveness: Reads text calmly without contextual understanding of urgency or emotion in content
Kokoro 82M v1.0
Best for: Budget-conscious developers comfortable with open-weight models.
Kokoro 82M v1.0 ranks #9 on
Artificial Analysis with ELO 1,059, making it the highest-ranked open-weight model on the leaderboard. Released January 2025 with 6,277 comparison samples, the model costs just $0.70 per 1M characters.
Pricing
$0.70 per 1M characters represents the cheapest option on the leaderboard. Price-performance ratio of 1,513 ELO per dollar (1,059 ELO ÷ $0.70) leads all models, though absolute quality ranks 104 points below Inworld.
Pros
- Lowest Cost: Cheapest TTS option on leaderboard by significant margin
- Open Weights: Open-source model enables customization and self-hosting
- Top Open Model: Highest-ranked open-weight option demonstrates strong community development
Cons
- Lower Quality: Ranks 104 ELO points below Inworld despite cost advantage
- Self-Hosting Required: Open-weight model requires infrastructure setup versus managed API services
Cartesia Sonic 3
Best for: Applications requiring absolute minimum time-to-first-audio.
Cartesia Sonic 3 ranks #10 on
Artificial Analysis (ELO 1,054), 109 points below Inworld. According to
Cartesia's documentation, the service achieves 40ms time-to-first-audio with 90ms model latency—4x faster than next alternative—using State Space Model architecture that scales linearly versus quadratic transformer costs.
WebSocket multiplexing supports dozens of concurrent generations. Instant voice cloning works from 3 seconds of audio across 40+ languages with fine-grained emotion, volume, and speed controls.
Pricing
Per
Cartesia pricing, Sonic-3 costs $46.70 per 1M characters (4.67x Inworld's price). Free tier includes 10,000 credits with no commercial use. Pro plan offers $5/month with 100,000 credits and 3 parallel requests.
Pros
- Fastest TTFA: 40ms time-to-first-audio represents industry's lowest benchmark for immediate response applications
- Efficient Architecture: State Space Models achieve 2x faster inference speed and 4x higher throughput versus transformers
Cons
- Character Limits: 500-character limit for English on Sonic Turbo requires splitting longer texts into chunks
- Mid-Tier Quality: Ranks 109 ELO points below Inworld despite costing 4.67x more per million characters
Microsoft Azure Neural
Best for: Microsoft ecosystem teams requiring enterprise Azure integration.
Microsoft Azure Neural ranks #11 on
Artificial Analysis with ELO 1,051, placing it 112 points below Inworld. Released September 2018, it represents the longest-established neural TTS on the leaderboard with 8,898 comparison samples—the second-highest sample size after ElevenLabs.
Pricing
$15 per 1M characters (1.5x Inworld's price). Price-performance ratio of 70.1 ELO per dollar (1,051 ELO ÷ $15) trails Inworld's 116.3.
Pros
- Azure Integration: Deep integration with Microsoft ecosystem and enterprise services
- Established Track Record: Longest-running neural TTS with extensive production validation
Cons
- Mid-Tier Quality: Ranks 112 ELO points below Inworld at 1.5x the price
- Aging Technology: 2018 release date suggests older architecture versus newer streaming-native models
Resemble AI Chatterbox HD
Best for: Teams seeking mid-tier quality with moderate pricing.
Resemble AI Chatterbox HD ranks #12 on
Artificial Analysis with ELO 1,050, placing it 113 points below Inworld. Released May 2025 with 5,845 comparison samples, the model costs $40 per 1M characters.
Pricing
$40 per 1M characters (4x Inworld's price). Price-performance ratio of 26.3 ELO per dollar (1,050 ELO ÷ $40) significantly trails Inworld's 116.3.
Pros
- Solid Sample Size: 5,845 comparison votes indicate meaningful validation
Cons
- Poor Price-Performance: 4x more expensive than Inworld while ranking 113 ELO points lower
Google Cloud Studio
Best for: Multinational enterprises requiring 75+ languages within GCP infrastructure.
Google Studio voices rank #13 on
Artificial Analysis (ELO 1,048), 115 points below Inworld. The service offers 380+ voices across 75+ languages with WaveNet/Neural2 achieving 200-250ms latency in
third-party benchmarks.
Chirp 3 HD voices support 30+ styles with low-latency streaming. Deep integration with Dialogflow, Contact Center AI, and Assistant provides comprehensive cloud infrastructure.
Pricing
Per
Google Cloud pricing, Studio voices cost $160 per 1M characters (16x Inworld's pricing). Standard voices run $4 per 1M with 4M free/month. WaveNet/Neural2 voices cost $16 per 1M with 1M free/month. New customers receive $300 free credits.
Pros
- Broadest Language Coverage: 380+ voices across 75+ languages/variants provides unmatched global reach for multinational applications
Cons
- Infrastructure Overhead: Requires Google Cloud Platform setup (Storage, Functions, IAM) adding complexity versus standalone TTS APIs
- Premium Pricing: Studio voices at $160/1M chars make it 16x more expensive than Inworld for equivalent volume
Hume AI Octave 2
Best for: Emotionally adaptive AI companions requiring natural language emotion control.
Hume AI Octave 2 ranks #14 on
Artificial Analysis (ELO 1,046), 117 points below Inworld. According to
Hume's documentation, the first TTS system built on LLM intelligence understands context emotionally, accepting natural language instructions like "sound sarcastic" or "whisper fearfully."
Octave 2 preview delivers ~100ms latency (200ms TTFT with streaming). EVI 3 enables speech-to-speech responses under 300ms. Voice cloning works from 15 seconds of audio.
Pricing
Per
Hume pricing, Octave 2 costs $7.60 per 1M characters (cheapest among top 15 providers). Free tier includes 10,000 chars/month. Starter plan offers $3/month with 30,000 chars. Business tier provides $500/month with 10M chars at $0.05/1,000 overage.
Pros
- Emotional Intelligence: LLM-based architecture understands context emotionally, enabling natural language emotion control versus manual SSML tags
- Cost Leadership: $7.60/1M chars represents cheapest pricing among top 15 quality providers
Cons
- Lower Quality: Ranks 117 ELO points below Inworld despite similar pricing to Inworld TTS-1.5-Max
- Limited Language Support: 11 languages versus competitors offering 70+ restricts global deployment options
Speechify Simba
Best for: Teams seeking Inworld-equivalent pricing with lower quality.
Speechify Simba ranks #15 on
Artificial Analysis with ELO 1,037, placing it 126 points below Inworld. Released June 2024 with 6,322 comparison samples, the model costs $10 per 1M characters, matching Inworld TTS-1.5-Max pricing.
Pricing
$10 per 1M characters matches Inworld TTS-1.5-Max. Price-performance ratio of 103.7 ELO per dollar (1,037 ELO ÷ $10) trails Inworld's 116.3 despite identical pricing.
Pros
- Competitive Pricing: Matches Inworld TTS-1.5-Max pricing tier
Cons
- Significantly Lower Quality: Ranks 126 ELO points below Inworld at identical price point
Additional Ranked Providers (16-26)
The following providers round out the top 26 on
Artificial Analysis:
16. Maya Research Maya1 (Open) - ELO 1,026, pricing not available
17. NVIDIA Magpie 357M (Open) - ELO 1,014, pricing not available
18. Zyphra Zonos v0.1 (Open) - ELO 1,000, $20 per 1M chars
19. LMNT - ELO 987, $43.60 per 1M chars
20. Murf AI Speech Gen 2 - ELO 984, $100 per 1M chars
21. Alibaba Qwen3 TTS Flash - ELO 978, $10 per 1M chars
22. OpenVoice v2 (Open) - ELO 978, $8.30 per 1M chars
23. Neuphonic TTS - ELO 949, $17.60 per 1M chars
24. Coqui XTTS v2 (Open) - ELO 915, $40.40 per 1M chars
25. StyleTTS 2 (Open) - ELO 907, $2.80 per 1M chars
26. MetaVoice v1 (Open) - ELO 829, pricing not available
Why Inworld AI delivers real-time voice without compromise
Sub-250ms latency enables natural conversation turn-taking without perceptible delay.
#1 rankings on Artificial Analysis and HuggingFace prove consistent quality leadership with 59-61% win rates versus ElevenLabs, Cartesia, and OpenAI in blind preference tests.
Bible Chat case study demonstrates scaling to millions of users at approximately 5% of competitor costs. $5-10/million characters translates to under 1 cent per minute of generated audio. Zero-shot voice cloning comes free with no per-clone licensing fees.
The
full training framework is open-sourced from codec to SpeechLM fine-tuning. Streaming-native architecture eliminates batch processing bottlenecks. Quantization-aware training maintains quality at reduced compute costs while developers validate claims through reproducible benchmarks.
Where hyperscalers optimize for infrastructure reliability and specialists chase single metrics,
Inworld eliminates the traditional tradeoff between quality, latency, and cost through fundamental architectural breakthroughs.
How we evaluated the best TTS APIs
Benchmarks and pricing reflect data available as of January 2026 and may change. Vendor specifications, third-party testing, and independent leaderboards inform our analysis. Where possible, we anchor claims to primary sources.
Time to first byte (TTFB) and time to first audio (TTFA) measurements determine real-world responsiveness. Sustained latency under multi-session load (p50, p90, p99 percentiles) reveals production performance versus advertised inference-only speeds.
Quality rankings from HuggingFace TTS Arena and
Artificial Analysis Speech Leaderboard use blind comparison tests. Per-character and per-minute pricing across self-serve tiers exposes true costs, while hidden infrastructure fees (cloud storage, egress, function triggers) add overhead for hyperscaler solutions.
SDK availability (Unity, Unreal, Node.js, Python) determines development ease. WebSocket streaming versus REST-only APIs separates real-time applications from batch processing. Documentation quality, example code, and production deployment guides reveal integration complexity.
Voice cloning (zero-shot versus professional fine-tuning requirements), emotional expressiveness (SSML, audio markups, natural language instructions), lipsync support (speech marks, visemes, timestamp alignment), and deployment flexibility (cloud, VPC, on-premise, offline containers) differentiate feature sets.
Published case studies with measurable outcomes (latency, cost, scale), third-party benchmarks, blind preference tests, community adoption signals (GitHub stars, integration partnerships), and enterprise customer references validate production readiness.
FAQs
What is a TTS API?
A cloud service that converts text -o-speech via HTTP or WebSocket. Neural models synthesize audio from written input. Inworld TTS delivers sub-200ms streaming for real-time applications.
How do I choose the right TTS API?
Match latency to your use case. Interactive applications need streaming and lipsync support. IVR and batch workflows prioritize reliability. Inworld balances quality, speed, and cost for production scale.
Is Inworld AI better than ElevenLabs?
Inworld ranks #1 on Artificial Analysis (ELO 1,163) at $10/M chars. ElevenLabs ranks #3 (ELO 1,108) at $206/M chars with 70+ languages. Inworld optimizes for real-time; ElevenLabs for content production and language breadth.
What latency do I need for real-time voice applications?
Sub-250ms maintains natural conversation flow. Sub-200ms works best for immersive experiences. Inworld achieves sub-200ms P90 end-to-end. Cartesia hits 40ms TTFA. ElevenLabs claims 75ms inference-only.
What's the difference between streaming and batch TTS?
Streaming (WebSocket) returns audio chunks during generation for real-time playback. Batch (REST) returns a complete file after processing. Real-time apps need streaming. Inworld, Cartesia, and ElevenLabs all support WebSocket.
How do I add lipsync to characters with TTS?
Use timestamp alignment (Inworld provides word/character-level), speech marks (Amazon Polly visemes), or SDK templates (Inworld Unity/Unreal). Timestamp data synchronizes mouth movements with audio output.
Which TTS API is cheapest for high-volume applications?
Kokoro: $0.70/M chars (open-weight). Inworld: $5-10/M. Hume: $7.60/M. OpenAI: $15/M. Google/AWS pricing often excludes infrastructure fees like storage, egress, and functions.
Can I use TTS APIs offline or on-premise?
Most are cloud-only. Inworld, Rime, IBM Watson, and Speechmatics offer on-premise deployment. Required for regulated industries (healthcare, finance) and low-latency edge computing.
Do TTS APIs support voice cloning?
Zero-shot (instant): Inworld (free), Cartesia (3 sec sample), Hume (15 sec). Professional cloning: ElevenLabs and Inworld (30+ min audio). Rime doesn't offer cloning.
What's the difference between TTS for voice agents versus interactive applications?
Voice agents prioritize accuracy, low hallucination rates, and pronunciation consistency. Interactive applications need lipsync, emotion control, and sub-200ms response. Inworld's SDKs support both.
Best alternatives to ElevenLabs for real-time applications?
Inworld: #1 quality ranking, sub-200ms latency, 90% cost savings. Cartesia: 40ms TTFA for extreme speed. Hume: emotional understanding for adaptive dialogue. Rime: sub-100ms on-prem for enterprise.