Short version: Cerebras is generally faster on big models, Groq is generally cheaper on the models both hosts serve, and both offer real no-card free tiers that make them the two easiest places to prototype fast inference in 2026. On our verified prices, Groq undercuts Cerebras on Llama 3.3 70B (0.79 dollars vs 1.20 dollars per 1M output tokens) and on gpt-oss-120b (0.60 dollars vs 0.75 dollars), while Cerebras holds the raw tokens-per-second crown on large models. Neither one is the cheapest host for these models overall, which matters if speed is not your constraint.
Groq and Cerebras are the two inference providers that built their own silicon instead of renting Nvidia GPUs, and both sell one thing above all else: speed. This post compares the hardware, the speed claims, our weekly re-checked prices, and the free tiers, so you can pick the right one for your workload.
Two different bets against the GPU
Both companies rejected the GPU paradigm, but they went in different directions.
- Groq built the LPU (Language Processing Unit), a deterministic chip designed for low-latency sequential token generation. The design goal is predictable, very fast time-to-first-token and high streaming throughput on open-weight models.
- Cerebras built the WSE-3, a wafer-scale engine that is essentially one giant chip the size of a dinner plate. Keeping an entire model's weights in on-chip memory removes the memory-bandwidth bottleneck that caps GPU inference speed.
The practical difference: Groq optimizes for latency and consistency, Cerebras optimizes for raw throughput on the largest models. Both expose OpenAI-compatible APIs, so switching between them (or away from either) is usually a base URL and model name change, not a rewrite.
Who is actually faster?
Speed numbers move with every model release and every software update, so treat specific figures as snapshots. The pattern in 2026 benchmarks is consistent, though:
- Cerebras has posted the headline numbers on large models: independent and vendor benchmarks have shown Llama 3.3 70B running at well over 1,000 tokens per second, with claims of 1,800+ tokens per second, and Cerebras was the first to break 1,000 tokens per second on a 405B-parameter model.
- Groq typically lands in the several-hundred to low-thousands tokens-per-second range depending on the model, with very low and very consistent time-to-first-token, which is what interactive apps actually feel.
For most products the honest answer is that both are so far ahead of GPU-based hosts that the difference between them stops being the deciding factor. A chat UI streaming at 400 tokens per second and one streaming at 1,500 tokens per second both feel instant to a human reader. Where the gap does matter:
- Deep agent loops, where dozens of sequential model calls stack up and every step's latency compounds. Here Cerebras's raw throughput can visibly shorten end-to-end runs.
- Real-time voice, where time-to-first-token dominates. Groq's consistency is a real asset here, and it also serves Whisper Large v3 transcription at about 0.0019 dollars per minute, which Cerebras does not offer.
Verified prices: what each host charges
These are from our rankings dataset, which we re-check weekly against official pricing pages. Per 1M output tokens:
| Model | Groq | Cerebras | Cheapest anywhere |
|---|---|---|---|
| Llama 3.3 70B | 0.79 dollars | 1.20 dollars | 0.32 dollars (OpenRouter) |
| gpt-oss-120b | 0.60 dollars | 0.75 dollars | 0.17 dollars (DeepInfra) |
| Qwen3 235B A22B | not listed | 1.20 dollars | 0.40 dollars (Hyperbolic) |
| Llama 4 Scout | 0.34 dollars | not listed | 0.30 dollars (DeepInfra) |
| Llama 3.1 8B | 0.08 dollars | not listed | 0.05 dollars (DeepInfra, Novita) |
Three takeaways from the table:
- Groq is cheaper than Cerebras on both models they directly share in our data, by roughly 20 to 35 percent.
- Neither host is the cheapest place to run these models. On Llama 3.3 70B the cheapest verified endpoint runs less than half of Groq's price, and on gpt-oss-120b the gap to the cheapest host is more than 3x against both.
- You are explicitly paying a speed premium at both hosts. That premium is worth it for latency-sensitive traffic and wasted money on batch work.
The right mental model: route interactive, user-facing calls to a speed host, and route bulk work (evals, backfills, classification pipelines) to whichever provider is cheapest for that model that week. Our cheapest AI inference API guide covers the budget end of that split.
Free tiers: both real, differently shaped
Both providers let you start with no credit card, which puts them on the short list of genuinely free LLM API keys.
- Groq offers a no-card free tier gated by per-minute and per-day request and token limits that vary by model. It is an ongoing rate-limited allowance, not a one-time credit, so it refills and suits steady prototyping. We cover it in detail in our Groq free tier guide.
- Cerebras opened an unusually generous free tier in 2026: reports and its own docs describe a daily token allowance around 1M tokens per day with per-minute rate limits and a reduced context window on free-tier models. As with Groq, exact numbers shift, so verify in the Cerebras console before you build around them.
Practical read: Cerebras's free tier is currently one of the most generous daily allowances of any inference host, which makes it a strong default for side projects and agent experiments. Groq's free tier is smaller but has been stable for years and covers more model variety, including transcription. Both are covered alongside every other no-card key in our roundup of free LLM API keys.
Which one should you pick?
- Pick Cerebras if raw throughput is the point: long agent chains, code generation loops, or anywhere you are waiting on thousands of output tokens per call. Its free tier is also the more generous starting point right now.
- Pick Groq if you want lower prices on shared models, broader model coverage including Whisper transcription, and highly consistent latency for chat and voice products.
- Pick neither as your only host. Both are OpenAI-compatible, so the cost of keeping a cheap fallback provider configured is nearly zero, and for batch traffic a budget host will beat both on price by 2x or more.
Bottom line
Groq and Cerebras are the two hardware-first speed plays in inference, and both deliver on the speed promise. Cerebras wins the tokens-per-second benchmarks on big models and currently has the more generous free tier; Groq wins on price for the models both serve and on model breadth. Treat both as your latency tier, not your everything tier, and keep re-checking prices, because this market moves monthly. Our rankings track the cheapest verified endpoint per model and are re-checked weekly, and Perkstack members also get the full catalog of 200+ verified credits and free tiers, so browse the catalog or create an account to keep your inference stack current.
Related reading: free LLM API keys, the cheapest AI inference APIs, and DeepInfra vs Together.