Open weights
Downloadable weights you can run on your own hardware or cloud — no per-token API dependency on a vendor.
Open-weights 400B-parameter frontier model, self-hostable for on-prem deployments.
Llama 4 Behemoth is Meta's open-weights 400B-parameter frontier model, released in October 2025. Unlike the closed frontier models, its weights are downloadable — so you can self-host, fine-tune, and run it air-gapped.
That makes it the most credible open alternative to Opus and GPT-5 for teams that need data sovereignty, cost control at scale, or model customisation. The trade-off is that you take on the infrastructure, safety tuning, and operational burden yourself.
Downloadable weights you can run on your own hardware or cloud — no per-token API dependency on a vendor.
Full fine-tuning and LoRA adapters let you specialise the model on proprietary data and domains.
Runs fully on-prem or in air-gapped environments for regulated and classified workloads.
At high volume, self-hosted inference can be dramatically cheaper than frontier API pricing.
Running a frontier-class model entirely inside a secure, disconnected environment.
0data leaves your perimeterSpecialising the base model on proprietary clinical data without sending it to a third party.
fullfine-tuning controlServing very high request volumes on owned hardware to cap per-token cost.
10×cheaper at scale vs frontier APIsYou run the cluster. Serving a 400B model needs serious GPU hardware plus the MLOps to keep it reliable — a real operational cost.
Trails the best closed models slightly. On the hardest reasoning and agentic benchmarks it is close but a step behind Opus 4.7 and GPT-5.
No managed guardrails. Refusal behaviour, moderation, and abuse protection must be built and maintained by your team.
Yes — the weights are downloadable under Meta’s community license, so you can self-host and fine-tune rather than calling a hosted API.
As a 400B-parameter model it needs a multi-GPU server (or a managed cluster). Quantised builds reduce the footprint at some quality cost.
It is the strongest open alternative and competitive on most tasks, trading a small quality gap for sovereignty, fine-tuning, and cost control.
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