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Nathan Lambert Explains How Open Models Can Win on Cost
- Who
- Nathan Lambert
- What
- shared a practice recording of his talk How Open Models Win talk on the open model economy
- Quote
This is a practice recording of my talk "How Open Models Win" for Fireworks Forge 2026 in San Francisco (3 November 2026), which will have improvements over this one.
What happened
Nathan Lambert gave a talk on the open model economy, arguing open model builders should steer industry economics to avoid being swallowed by OpenAI and Anthropic. He says this depends on driving inference costs down dramatically on specialized, repetitive tasks rather than competing with frontier labs on cost in general agents. The talk covers open model usage, proximity to the frontier, mapping the open model economy, and how open models win.
Read next
See the full storyNathan Lambert shares practice recording on how open models can winNew talk on the open model economy. I wanted to break down the case of where open model builders should steer the economics of the industry, if we want to avoid being swallowed by OpenAI and Anthropic in due time. This rests fully on being able to drive the cost of inference down dramatically on specialized, repetitive tasks, rather than trying to compete on cost with the frontier labs in any general agent.
A core piece of it is how the open model economy is very fragmented, leaving an interesting puzzle we need to solve to get revenue from applications to feed back into the next model cycle. This is a very near-term problem as closed labs scale rapidly.
This talk investigates:
Are people using open models?
How close are open models to the frontier?
Mapping the open model economy
How open models win
This is a practice recording of my talk "How Open Models Win" for Fireworks Forge 2026 in San Francisco (3 November 2026), which will have improvements over this one.
The story so far
Nathan Lambert shared a practice recording of his “How Open Models Win” talk, arguing that open model builders can shape the industry’s economics by sharply lowering inference costs for specialized, repetitive tasks. He said they should focus there rather than try to beat frontier labs on cost for general agents. The recording was a practice version for Fireworks Forge 2026 in San Francisco; Lambert said the talk at the event would include improvements.
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