Llama 4 Maverick vs o1-pro compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
| Spec | Llama 4 Maverick | o1-pro | Winner |
|---|---|---|---|
| Maker | Meta | OpenAI | – |
| Type | Open-weight | Proprietary | |
| Context window | 1M tokens | 200K tokens | |
| Input price | $0.2/M · free self-host | $150/M | |
| Output price | $0.7/M · free self-host | $600/M | |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | No | |
| Self-hostable | Yes | No (API only) | |
| License | Llama Community | Proprietary |
Llama 4 Maverick is ~857× cheaper than o1-pro on output tokens ($0.7 vs $600 per M tokens).
| Capability | Llama 4 Maverick | o1-pro |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✗ |
| 1M+ context window | ✓ | ✗ |
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
| Criterion | Llama 4 Maverick | o1-pro |
|---|---|---|
| Cost-efficiency | 5.0 | 2.0 |
| Context window | 5.0 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 3.5 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide...
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Llama 4 Maverick is open-weight and competitive on many tasks, but o1-pro may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Yes. Llama 4 Maverick has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. o1-pro is API-only and cannot be self-hosted.
Llama 4 Maverick costs $0.7/M output vs $600/M for o1-pro — roughly 857x cheaper via API, and free if you self-host.
Choose Llama 4 Maverick if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose o1-pro if you want frontier capability through a managed API with zero infrastructure to run.
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