o3-mini vs Sonar Large
A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.
Updated
o3-mini specs · Sonar Large specs- PriceSonar Large
Sonar Large is roughly 4.4× cheaper on output tokens ($1.00 vs $4.40 per 1M).
- Context windowo3-mini
o3-mini accepts 200K tokens vs 127K, 1.6× the room for long documents and codebases.
- BenchmarksTie
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.
- ModalitiesTie
Both handle text.
- OpennessTie
Both are closed-weight, API-only.
It's a genuine coin-flip between o3-mini and Sonar Large: 1 category wins each, with the rest tied. Sonar Large is roughly 4.4× cheaper on output tokens ($1.00 vs $4.40 per 1M). o3-mini accepts 200K tokens vs 127K, 1.6× the room for long documents and codebases.
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. Both target the same set of modalities (text), so the deciding factors are price, context, and raw quality. Both are closed-weight, API-only.
o3-mini is the newer of the two, released 2 months after Sonar Large, which usually means a more recent knowledge cutoff and updated safety post-training. o3-mini is usually picked for reasoning and math workloads, while Sonar Large sees more deployments in research agent and rag. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.
Side-by-side specs
| Spec | o3-mini | Sonar Large |
|---|---|---|
| Provider | OpenAI | Perplexity |
| Released | Jan 2025 | Nov 2024 |
| Modalities | text | text |
| Context window | 200K tokens | 127K tokens |
| Max output | , | , |
| Input · 1M | $1.10 / 1M tokens | $1.00 / 1M tokens |
| Output · 1M | $4.40 / 1M tokens | $1.00 / 1M tokens |
| Knowledge cutoff | 2023-10 | , |
| Open weights | No | No |
| API available | Yes | Yes |
Pricing at scale
What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.
- Light usage, 100k in / 50k out per day$9.90 vs $4.50
- Heavy usage, 1M in / 500k out per day$99.00 vs $45.00
- RAG workload, 5M in / 200k out per day$191 vs $156
Light usage, 100k in / 50k out per day: $9.90 vs $4.50 per month, model B comes out ahead. Heavy usage, 1M in / 500k out per day: $99.00 vs $45.00 per month, model B comes out ahead. RAG workload, 5M in / 200k out per day: $191 vs $156 per month, model B comes out ahead.
Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.
- o3-mini$0.330
- Sonar Large$0.150
Benchmarks compared
Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.
- GPQA79.7
o3-mini fits when…
- Reasoning at mid-tier cost
- Fast for a thinking model
- Long-context tasks, handles 200K tokens vs 127K for Sonar Large.
Sonar Large fits when…
- Web-search grounded
- Citation-first output
- Cheap
- Cost-sensitive workloads, 4.4× cheaper than o3-mini on output tokens.
Consider GPT-5.5
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Frequently asked
Is o3-mini or Sonar Large cheaper?
Sonar Large is cheaper at $1.00 / 1M tokens per million output tokens, vs $4.40 / 1M tokens for o3-mini.Which has the larger context window?
o3-mini accepts 200K tokens vs 127K for Sonar Large.Is o3-mini or Sonar Large better for coding?
Both o3-mini and Sonar Large are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.Are either of these models open source?
Neither model ships open weights, both are accessible only via their respective providers' APIs.When were o3-mini and Sonar Large released?
o3-mini was released by OpenAI on 2025-01-31. Sonar Large was released by Perplexity on 2024-11-19.
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