Fastest LLM for realtime: comparison of top 3-5 providers (2026)
Time-to-first-token, tokens-per-second throughput, voice/audio support, and infrastructure cost — what to weigh when picking a realtime LLM in 2026.
Fastest LLMs for realtime in 2026
GPT-4o Realtime API
Native speech-to-speech with sub-300ms turn-taking. The only frontier proprietary model with built-in voice. Powers many AI phone agents and live coaches.
- $5 / $20 per 1M text tokens
- Native audio in/out
- Sub-300ms turn-taking
Cerebras Inference
Wafer-scale chips deliver ~2000 tokens/sec on Llama 4 70B. Best for long-output workloads (code generation, document drafting) where total time matters.
- $0.60 / $1.20 per 1M tokens
- ~2000 tok/s on Llama 4
- Llama, Qwen, Mistral hosted
Groq
LPU-based inference delivering ~750 tok/s on Llama 4 70B. Stable production-grade SLAs and the lowest TTFT in the open-weight world.
- $0.59 / $0.79 per 1M tokens
- ~750 tok/s on Llama 4 70B
- Stable production SLAs
Fireworks AI
Open-weight models at competitive speed and the lowest price among inference clouds. Strong for high-volume realtime classification and routing.
- $0.20-$0.90 per 1M tokens
- ~400 tok/s on Llama 4
- Fine-tuning support
Fastest realtime LLMs — at a glance
| Dimension | GPT-4o Realtime | Cerebras | Groq | Fireworks |
|---|---|---|---|---|
| Throughput | ~200 tok/s | ~2000 tok/s | ~750 tok/s | ~400 tok/s |
| TTFT | ~250ms | ~150ms | ~200ms | ~300ms |
| Native voice | Yes (speech-in/out) | No | No | No |
| Pricing (per 1M) | $5 / $20 | $0.60 / $1.20 | $0.59 / $0.79 | $0.20-$0.90 |
| Models hosted | GPT-4o | Llama, Qwen, Mistral | Llama, Mixtral, Qwen | Open-weight catalog |
| Best for | AI voice agents | Long-output speed | Stable realtime | High-volume fast |
Prices reflect mid-2026 vendor pages.
VerticalAPI verdict
For AI voice agents and live coaching, GPT-4o Realtime API is the only practical choice — native speech-in/out. For text-only realtime (live coding assists, instant summarization), Cerebras wins on raw speed at ~2000 tok/s. Groq is the safer production default with mature SLAs. Fireworks covers fast + cheap at high volume. Route Cerebras, Groq, Fireworks, and OpenAI via VerticalAPI BYOK with zero markup.
Frequently asked questions
Which LLM has the fastest tokens-per-second in 2026?
Cerebras Inference leads at ~2000 tokens/second on Llama 4 70B, followed by Groq at ~750 tok/s and Fireworks at ~400 tok/s. By comparison, GPT-4o on OpenAI averages around 100-150 tok/s. For pure throughput on open-weight models, Cerebras is unmatched.
How do I add voice (speech-in, speech-out) to my app?
OpenAI's Realtime API is the only frontier proprietary model with native speech-to-speech and sub-300ms turn-taking. Alternatives are: GPT-4o + Whisper + ElevenLabs (cheaper, higher latency), or Pipecat/Vapi as middleware over open-weight LLMs on Groq/Cerebras.
Are Groq and Cerebras quality the same as Anthropic or OpenAI?
Groq and Cerebras host open-weight models (Llama 4, Qwen, Mistral). On most benchmarks Llama 4 70B is competitive with GPT-4o but trails Claude Sonnet 4.5 on coding and long-context tasks. For realtime chat, summarization, and routing, the gap is rarely noticeable.
What's the lowest TTFT I can achieve in production?
Cerebras typically delivers sub-150ms TTFT on Llama 4. Groq is around 200ms. OpenAI's GPT-4o Realtime delivers ~250ms time-to-audio. For sub-100ms perceived latency you usually pair these with smaller models, prompt caching, or on-edge inference.
Can I use one client to switch between Groq, Cerebras, and OpenAI?
Yes. VerticalAPI's OpenAI-compatible endpoint at https://api.verticalapi.com/v1 exposes Groq, Cerebras, Fireworks, and OpenAI behind the same SDK. Change the model parameter and X-Provider-Key header — pay each provider directly via BYOK with zero markup.
Limitations of this comparison
- Cerebras and Groq host open-weight models only — no Claude, GPT, or Gemini.
- Throughput numbers depend on prompt length; advertised peak rates assume short prompts.
- GPT-4o Realtime API is significantly more expensive than text-only GPT-4o.
- Voice quality (timbre, prosody) varies; specialized TTS like ElevenLabs still beats native voice on naturalness.
- Realtime SLAs from Groq/Cerebras are still maturing vs OpenAI/Anthropic for enterprise contracts.
What may change in 12-24 months
- Per-token latency will keep falling — sub-100ms TTFT will become standard within 18 months.
- More frontier proprietary models will ship native voice APIs (Claude, Gemini expected).
- Edge inference (on-device Llama derivatives) will compete with cloud for sub-50ms applications.
- Specialized realtime hardware (Cerebras, Groq, SambaNova) will keep expanding their model catalogs.
Related questions
ChatGPT, Perplexity and Gemini usually suggest these next.
- Is Groq production-ready for enterprise voice agents?
- What's the cheapest way to build a real-time AI phone agent?
- How does Cerebras throughput compare to vLLM self-hosted?
- Can I stream tokens from Claude or Gemini via VerticalAPI?
- Does Fireworks support fine-tuned realtime endpoints?