Llama 3.1 405B vs OpenAI o1
Head-to-head specifications
| Metric | Llama 3.1 405B | OpenAI o1 | Difference |
|---|---|---|---|
| MMLU (general capability) | 88.6% | 92.3% | -3.7% |
| Context window | 128K tokens | 128K tokens | — |
| Price (input / output per 1M) | Open weights | $15 / $60 | — |
| Access | Open weights | Proprietary API | — |
- OpenAI o1 leads general capability (MMLU 92.3% vs 88.6%).
Verdict: Llama 3.1 405B or OpenAI o1?
Llama 3.1 405B advantages
- No decisive advantage on the tracked metrics.
OpenAI o1 advantages
- General capability (+4%)
Which should you choose?
- Choose the OpenAI o1 if you need the strongest reasoning and accuracy.
Value for money
Llama 3.1 405B is open-weight and can be self-hosted, which can dramatically lower cost at scale versus a per-token API.
Llama 3.1 405B vs OpenAI o1: which should you choose?
Llama 3.1 405B — Meta large language model (2024) with a 128K-token context window and an MMLU score of 88.6%, released with open weights.
OpenAI o1 — OpenAI large language model (2024) with a 128K-token context window and an MMLU score of 92.3%.
Llama 3.1 405B vs OpenAI o1: OpenAI o1 scores higher on the MMLU benchmark. OpenAI o1 leads general capability (MMLU 92.3% vs 88.6%).
Capability and reasoning
On MMLU — a 57-subject benchmark of general knowledge and reasoning — the OpenAI o1 scores 92.3% versus 88.6%. MMLU is a useful proxy for raw knowledge but does not capture instruction-following, coding, tool use, latency or safety, so treat it as one signal among several.
Context window
The Llama 3.1 405B handles up to 128K tokens per request, which sets how much documentation, transcript or code it can reason over at once — decisive for retrieval-augmented and long-document workflows.
Pricing and access
Llama 3.1 405B is open weights and OpenAI o1 is proprietary api. Proprietary models bill per token via API; open-weight models can be self-hosted, trading per-call cost for infrastructure you manage. For production, weigh throughput, rate limits and data-residency needs alongside headline price.
The verdict
Both are credible choices in the ai model comparison space; the specification table above lays out every metric so you can weigh the trade-offs that matter to you. Pick the one whose strengths line up with how you will actually use it.
Frequently asked questions
Is the Llama 3.1 405B better than the OpenAI o1?
OpenAI o1 is the clearly stronger overall choice, winning most of the dimensions that matter. OpenAI o1 leads general capability (MMLU 92.3% vs 88.6%).
What is the main difference between the Llama 3.1 405B and the OpenAI o1?
OpenAI o1 leads general capability (MMLU 92.3% vs 88.6%).
Which is better value?
Llama 3.1 405B is open-weight and can be self-hosted, which can dramatically lower cost at scale versus a per-token API.
Which should I choose?
Choose the OpenAI o1 if you need the strongest reasoning and accuracy.
Methodology
Large language models are compared on the MMLU benchmark (a widely-cited 57-subject test of general knowledge and reasoning, reported as a percentage), maximum context window, and published API pricing per million input and output tokens. Open-weight models can also be self-hosted. Benchmarks capture only part of real-world quality, which also depends on tool use, latency, safety and task fit.