TheFastest.ai
Real-time LLM speed benchmarks: TTFT, TPS, total time, updated daily.
If you need latency data to pick an LLM provider for chatbots or streaming apps, this is your go-to source. It’s free, transparent, and daily-refreshed. But remember: speed isn’t everything—pair with quality and cost benchmarks.
- Developers comparing LLM latency for real-time chatbots
- DevOps engineers optimizing model deployment locations
- Product managers evaluating user-facing AI response speed
- SRE teams selecting providers based on throughput metrics
- Users needing quality or accuracy benchmarks
- Those looking for production API access or integrations
- Teams requiring SLA-backed performance guarantees
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In short
TheFastest.ai — Real-time LLM speed benchmarks: TTFT, TPS, total time, updated daily. Best for Developers comparing LLM latency for real-time chatbots, DevOps engineers optimizing model deployment locations, Product managers evaluating user-facing AI response speed. Free to use.
Viability Score
How likely is TheFastest.ai to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Daily updated LLM speed benchmarks (TTFT, TPS, total time)
- Multi-region testing: US West, US East, Europe
- Filter by model (Llama 3.1 405B, GPT-4, Claude 3, Gemini)
- Filter by prompt type: text, function, image, audio
- Standardized 1000 input / 20 output token benchmarks
- Best-of-three runs removes outlier queuing delays
- Connection warmup eliminates HTTP setup latency
- Raw benchmark data in public GCS bucket
- Open-source benchmarking tools on GitHub
- Website source code on GitHub
- Request new models via GitHub issues
- Switchable light/dark mode
About TheFastest.ai
TheFastest.ai is a free, daily-updated benchmarking site that measures the real-world speed of popular large language models across multiple cloud providers. It tracks three core metrics: Time To First Token (TTFT), Tokens Per Second (TPS), and total response time. Built for developers and businesses deploying latency-sensitive AI applications, it runs tests from data centers in US West, US East, and Europe using a standardized methodology: a warmup connection, ~1000 input tokens, 20 output tokens, and best-of-three runs to remove outliers. The site offers filtering by model name (e.g., Llama 3.1 405B, GPT-4, Claude 3, Gemini) and prompt type (text, function, image, audio). Raw data is publicly available in a GCS bucket, and the benchmarking code is open-source on GitHub. Created by Fixie in Seattle, it provides an objective speed-only comparison—no quality or cost metrics—making it a complement to broader evaluation tools.
Behind the Verdict
TheFastest.ai fills a narrow but critical gap: real-world LLM latency benchmarks that are up to date and reproducible. We'd reach for this when choosing between providers for a real-time chatbot or voice interface where sub-second responses matter. The multi-region testing is a standout—latency from Europe vs US East can swing provider choice. The methodology is solid: warmup connections and best-of-three runs minimize noise, though the fixed 20-token output is more conversational than production (which often streams much longer). Where it bites: no quality or cost data. You might pick a fast model that’s expensive or dumber than alternatives. Compare to Artificial Analysis or OpenRouter—they bundle price and quality but update less frequently. TheFastest.ai wins on speed data freshness and transparency. Caveat: non-technical users may find the interface sparse. Overall, essential for LLM ops teams but not a replacement for broader evals.
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Use Cases
- Compare TTFT of GPT-4, Claude 3, and Gemini across US and EU regions before choosing a provider for your chatbot.
- Filter by provider and model to find the fastest option for real-time audio transcription with LLMs.
- Use the public dataset to automate latency monitoring in your CI/CD pipeline.
- Identify which model gives the best tokens-per-second for high-throughput text generation tasks.
- Benchmark your own model by filing a GitHub issue and seeing it appear in daily updates.
Limitations
- The benchmarks use a single fixed input length (~1000 tokens) and output length (20 tokens), which may not represent all use cases.
- Only speed metrics are measured; there is no evaluation of response quality, safety, or cost.
- The data is updated daily but may not reflect real-time fluctuations.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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