The open market for production LLM inference
Bucharest
Joined October 2026
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llm.buzz is the open market for production inference.
Providers compete on price and speed to give you the best prices on the market.
Building with models: one API, every model, the cheapest healthy provider on each request.
Serving models: list your endpoint, set your price, keep 100%. Your own model too.
9 text models on llm.buzz have an EU provider live right now.
Put the EU tags in provider.only and the request goes only to those providers.
Failover stays inside that list.
GLM-5.3, Mistral Medium 3.5, Qwen3.8 27B, gpt-oss-120b and 5 more, as of 18:18 UTC.
Sell your own model on llm.buzz. We take 0% of your price.
Apply once, list it from your endpoint and set five prices: input, output, cached input, cache write, reasoning.
We approve a new model once. An automated check sends real requests, and it goes live when it passes.
Mistral Medium 3.5 on llm.buzz: $1.19 in, $5.95 out per 1M tokens.
@MistralAI's own API: $1.50 / $7.50.
That's 20% under, as an Auto deal.
The lowest price we track for it, as of 07:19 UTC.
84 models on llm.buzz, and any of them can take another seller.
If you serve one for less than the price you see, list your endpoint next to it.
Apply once and you set the price. An automated check sends real requests, and the listing goes live when it passes.
We take 0%.
Open weights with no third-party host yet:
Mistral Large 4 from @MistralAI: 1.05T total, 52B active, 1M context.
Flint from @Recursive_SI: 40B total, 2.5B active, Apache 2.0.
Serving one? List it on llm.buzz. The first seller sets the price.
Claude Sonnet 5 on llm.buzz: $1.60 in, $8 out per million tokens.
@AnthropicAI list: $2 in, $10 out.
Cache reads $0.16, 20% off as an Auto deal.
Prices as of 10:16 UTC today.
Mistral Large 4 went open weights today. 1.05T total, 52B active, 1M context.
The release from @MistralAI takes text and image input.
If you're serving it, list it on llm.buzz. You set the price, an automated check runs, and it goes live when it passes. We take 0%.
