Editorial illustration for Cerebras Leads Top 5 Fast LLM APIs with Low Latency, High Token Rate
Cerebras Shatters LLM Speed Record at 2,500 Tokens/Sec
Cerebras Leads Top 5 Fast LLM APIs with Low Latency, High Token Rate
Cerebras has just clinched the top spot among the five fastest large‑language‑model APIs, a claim that hinges on two metrics most engineers watch: latency and token throughput. While many providers brag about raw speed, few can keep the initial response time short enough to keep interactive apps snappy. That balance matters when you’re feeding a model hundreds of words for a single request or handling a flood of queries in a production environment.
In practice, developers looking to stitch together long‑form summaries, pull out structured data, or spin up code‑generation services need a backend that won’t choke under sustained load. The ranking also highlights how Cerebras’ hardware‑software stack differs from the cloud‑centric offerings that dominate the market. By delivering a high token‑per‑second rate without sacrificing the first‑token pause, the platform positions itself as a practical option for any workload where raw throughput is the bottleneck.
The result is extremely fast token generation while still keeping first‑token latency low…
The result is extremely fast token generation while still keeping first-token latency low. This architecture makes Cerebras a strong choice for workloads where tokens per second matter most, such as long summaries, extraction, and code generation, or high-QPS production endpoints. Example performance highlights: - 3,115 tokens per second on gpt-oss-120B (high) with ~0.28s first token - 2,782 tokens per second on gpt-oss-120B (low) with ~0.29s first token - 1,669 tokens per second on GLM-4.7 with ~0.24s first token - 2,041 tokens per second on Llama 3.3 70B with ~0.31s first token What to note: Cerebras is clearly speed-first.
Looking at the data, Cerebras occupies the top spot among the five fastest LLM APIs, boasting low latency and a high token‑per‑second rate. Its custom Language Processing Unit, similar in intent to Groq’s LPU, delivers “extremely fast token generation while still keeping first‑token latency low,” according to the vendor. That makes the service attractive for long‑form summarisation, information extraction, code generation, and high‑QPS production endpoints.
Yet, the article does not quantify how these speeds compare to competing providers beyond the ranking, leaving the practical impact on end‑users somewhat unclear. The broader trend—open‑source models pushing past previous speed limits—suggests real‑time interaction and lengthy coding tasks are becoming more feasible. Still, whether the performance gains translate into cost‑effective, scalable SaaS deployments remains to be demonstrated.
In short, Cerebras’ architecture appears well‑suited for token‑intensive workloads, but further evidence is needed to confirm its advantage in diverse production environments. Developers will likely weigh these metrics against integration complexity and pricing models before committing.
Further Reading
- Cerebras Beats NVIDIA Blackwell: Llama 4 Maverick Inference - Cerebras
- Cerebras Shatters Inference Records: Llama 3.1 405B Hits 969 Tokens Per Second, Redefining Real-Time AI - TokenRing AI
- Cerebras WSE-3 Shatters LLM Speed Records as Q2 2026 IPO Approaches - TokenRing AI
- The Token Arbitrage: Groq vs. DeepInfra vs. Cerebras vs Fireworks ... 2025 Benchmark - GopenAI
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Common Questions Answered
How fast can Cerebras run OpenAI's gpt-oss-120B model?
Cerebras can run the gpt-oss-120B model at a record-breaking 3,000 tokens per second, which is a major advance in AI inference speed. This performance eliminates GPU memory bandwidth bottlenecks and dramatically reduces wait times for high-intelligence AI reasoning tasks.
What makes the OpenAI gpt-oss-120B model unique?
The gpt-oss-120B is OpenAI's first open-weight reasoning model released under the Apache 2.0 license, offering full transparency and customization capabilities. It achieves near-parity with top proprietary models like Gemini 2.5 Flash and Claude Opus 4, while providing unprecedented speed and cost efficiency.
What are the pricing details for Cerebras' gpt-oss-120B inference?
Cerebras offers the gpt-oss-120B model at $0.25 per million input tokens and $0.69 per million output tokens. This pricing represents a significant cost advantage compared to other proprietary models, making it an attractive option for developers and organizations seeking high-performance AI inference.