Best AI Infrastructure Providers for Real-Time Inference
The short answer
For real-time inference, the provider is chosen by output speed (tokens per second), how often requests queue or fail at peak, and whether you can buy guaranteed capacity. As of October 10, 2026:
- Cerebras — the fastest output available as a public API: gpt-oss-120b at about 3,000 tokens per second, Qwen 3.8 27B at about 1,850.
- Groq — fast and the cheapest for gpt-oss-120b: about 500 tokens per second at $0.15 / $0.60 per million tokens.
- Fireworks AI — the best way to run frontier open models (Kimi K3, GLM 5.3, DeepSeek V4.1 Flash) interactively, with Fast variants that target 100+ tokens per second and a Priority tier that is less likely to be load-shed.
- Together AI — the same open models plus provisioned throughput and dedicated endpoints (H100 $5.49, B200 $8.99 per GPU-hour) when serverless best-effort is not enough.
- Baseten — your own or fine-tuned models on dedicated, autoscaling deployments; custom SLAs on Enterprise.
This page is the real-time spoke of our best LLM inference providers ranking. Autoscaling and cold starts for custom models are covered in best inference API vendors for autoscaling.
The comparison
Prices are USD per million tokens (input / cached input / output) from each vendor’s own page on October 10, 2026.
| Provider | Real-time strength | Example model and speed | Price per MTok | Capacity you can guarantee |
|---|---|---|---|---|
| Cerebras | Highest tokens/second | gpt-oss-120b ~3,000 tok/s; Qwen 3.8 27B ~1,850 tok/s | gpt-oss-120b $0.35 / — / $0.75 | Dedicated Inference with production SLAs; shared tier for Free Trial and Pay as You Go |
| Groq | Fast and cheap small models | gpt-oss-120b ~500 tok/s, 131K context, 65K max output | $0.15 / $0.075 / $0.60 | Paid plans raise limits; enterprise capacity by contract |
| Fireworks AI | Frontier open models, interactive | Kimi K3 Fast, GLM 5.3 Fast (aim 100+ tok/s) | GLM 5.3 Fast $2.10 / $0.39 / $6.60 · Kimi K3 (Fast tier; standard $3 / $15) $4.50 / $0.45 / $22.50 · gpt-oss-120b $0.15 / $0.015 / $0.60 | Priority tier (service_tier: "priority"), on-demand GPUs |
| Together AI | Same models, committed capacity | Kimi K3, GLM 5.3, DeepSeek V4.1 Flash, gpt-oss-120B | gpt-oss-120B $0.15 / — / $0.60 · GLM 5.3 $1.40 / $0.26 / $4.40 | Provisioned throughput units (PTUs); dedicated H100 $5.49/h, B200 $8.99/h |
| Baseten | Custom and fine-tuned models | Your model on dedicated GPUs | Per GPU-minute; Model APIs per token | Pro: unlimited autoscaling, priority GPUs; Enterprise: custom SLAs |
What “real-time” means in numbers
A voice reply or an inline edit is usually 100–300 output tokens. At 3,000 tokens per second a 300-token answer streams in about a tenth of a second; at 500 it takes 0.6 seconds; at 100 it takes three seconds. That arithmetic is why voice agents and autocomplete gravitate to Cerebras and Groq, while chat products that can stream text to a reader are fine at Fireworks Fast speeds.
Output speed is only half of latency. The other half is time to first token, which grows with prompt length and with queueing at peak. Keep prompts short and stable so prompt caching works (Groq halves the price of cached input; Fireworks discounts it by up to 98% on DeepSeek V4.1 Flash), and keep the system prompt first so every request shares the cached prefix.
Picks by job
Voice agents and live assistants: Cerebras. Nothing else in a public API matches its output speed. The catch is the shared catalog: two models (gpt-oss-120b and Qwen 3.8 27B) and a 65K context on the free tier, 131K paid. Anything larger needs a Dedicated Inference contract.
Cheapest fast model: Groq. gpt-oss-120b at $0.15 / $0.60 with half-price cached input is the lowest-cost way to get sub-second short replies. Plan for rate limits on the base tier.
Real-time agents on a frontier open model: Fireworks AI. Kimi K3 Fast and GLM 5.3 Fast keep the same model quality at a higher price, and the Priority tier reduces the 503 load-shedding that users notice at peak. It is the most complete option for an interactive product built on Chinese or US open-weight frontier models.
A latency promise to your customers: Together AI or Baseten. Shared serverless is best-effort everywhere. Together sells provisioned throughput on its serverless models; Baseten runs your own model on dedicated deployments with autoscaling and, on Enterprise, custom SLAs and self-hosting in your cloud.
Closed models in real time. If the product needs Claude or GPT, use the vendors’ own speed tiers: Claude Opus 5.5 in fast mode (a premium tier; standard is $4 / $20) costs $8 / $40 per million tokens for up to 2.5x the speed, and OpenAI’s Fast mode is 2x the standard price, Ultrafast 6x (GPT-6 Astra standard $10 / $50 becomes $60 / $300 on the Ultrafast tier, up to 300 tokens per second). See our current API prices.
How to choose in four checks
- Measure p95, not averages, on your own prompt lengths at the hour you expect peak traffic.
- Check the model fits the catalog. The fastest hardware serves the fewest models; if you need Kimi K3 or GLM 5.3, the shortlist is Fireworks, Together or a dedicated deployment.
- Price the cached column. Real-time apps resend the same system prompt on every turn.
- Buy capacity before launch. Provisioned or dedicated capacity is what turns a fast demo into a service you can promise.
Related: best LLM serving providers for coding assistants and Baseten vs Together vs Fireworks.
Last verified: October 10, 2026. Speeds are the vendors’ published figures; measure on your own traffic.