Llama
Meta's open-weight model family (Llama 3.x). Common choice for self-hosted inference via Ollama or vLLM.
Vendor siteVendor certification
Certify your vendor page and info
Work at Llama? Send corrections with evidence. The editor checks the evidence, applies what holds up, and the page then carries a gold star showing the details were vendor-confirmed and checked on a date.
Certification is free. It is not an endorsement, a review score, or a ranking or placement boost, and it cannot be bought. What certification means.
Profile
- Journey stage
- Operations and data
- Ambition level
- Amplify
- Owned by
- Revenue Operations or Engineering or Operations
- Adoption level
- L4 Orchestrated
- Subcategory
- Foundation models
- Market position
- Incumbent
Ownership. Ownership varies by company. Engineering, Revenue Operations or Operations can own this. Pick one accountable owner before you buy, because a shared owner means no owner.
Incumbent. Established platform that predates the current AI wave and is already in most enterprise stacks. AI features here usually ship as an add-on to a seat you already pay for.
Evidence status: Vendor claim, no published case study found. Stage, level and seat are editorial mapping, not vendor statements.
Best for
Teams running their own inference for cost control, data residency, or provider redundancy.
Pricing model
Free / Open Weights
Known limitations
No public limitation documented as of 2026-10-01. Ask the vendor for caps on CRM fields written, supported objects, data lookback, and plan gating in writing.
What teams use it for
- Self-hosted chat
- Local agent backbone
- Air-gapped inference
What it claims to do
- Self-hosted chat
- Local agent backbone
- Air-gapped inference
Claimed benefit. Teams running their own inference for cost control, data residency, or provider redundancy.
Named use case. Self-hosted chat
What has to be true before you buy
- 01The friction is genuinely at operations and data. Buying at the wrong stage moves the bottleneck, it does not remove it.
- 02Ownership varies by company. Engineering, Revenue Operations or Operations can own this. Whoever it is owns the outcome, not just the licence. Unowned tools are adopted for a quarter and then quietly turned off.
- 03A human still signs off on the output. Write down who that is and what they are allowed to reject before rollout.
- 04L4 Orchestrated on the six-level AI Maturity Ladder. Multi-step work runs end to end, with a named owner and a measured result. This is the effort required for the workflow, not a product quality score.
- 05Pricing model on record: Free / Open Weights. Confirm the billable unit and what happens when volume doubles.
- 06We found no published case study for this tool, which does not prove none exists. Treat every number on the vendor site as a claim until you run your own baseline.
Teams named
- Engineering
- Revenue Operations
Similar tools
Scored on shared segment, tags, use cases, and owning team, not on category alone. Tools that only share a broad category are left out.
- GemmaChallengerSame subcategory: Foundation models; same tags, same use cases, same team
- Mistral AIIncumbentSame subcategory: Foundation models; same tags, same use cases, same team
- CohereIncumbentSame subcategory: Foundation models; same team
- GeminiIncumbentSame subcategory: Foundation models; same use cases, same team
- ClaudeIncumbentSame subcategory: Foundation models; same team
- OpenAIIncumbentSame subcategory: Foundation models; same team
Common questions about Llama
What is Llama used for?
Meta's open-weight model family (Llama 3.x). Common choice for self-hosted inference via Ollama or vLLM.
Who owns Llama inside a revenue team?
Ownership varies by company. Engineering, Revenue Operations or Operations can own this. Pick one accountable owner before you buy, because a shared owner means no owner. Teams named on the record: Engineering, Revenue Operations.
Where does Llama sit in the revenue journey?
Operations and data. Buy it only if that is the stage where the work actually breaks.
Is Llama an optimize, amplify, or reinvent move?
Amplify. A human still signs off on the output. Write down who that is and what they are allowed to reject before rollout.
How much effort does Llama take to adopt?
L4 Orchestrated on the six-level AI Maturity Ladder. Multi-step work runs end to end, with a named owner and a measured result. The level describes the workflow and adoption effort, not the quality of Llama.
What evidence exists for Llama?
We found no published case study for this tool. That does not prove none exists. Everything on this page is a vendor claim or an editorial mapping, not a Report benchmark.
How much does Llama cost?
Pricing model on record: Free / Open Weights. Confirm the billable unit and the overage rate before signing.
Category and stage mapping is editorial. Vendor claims are not Report benchmarks. Terms are defined in the AI and Revenue Dictionary.