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Model comparison
OpenAI's GPT-4.1 Nano against Perplexity's Sonar: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.
GPT-4.1 Nano lists at $0.175 per million tokens blended against $1.00 for Sonar - 5.7x less.
Intelligence index 8 against 8: within a point of each other.
GPT-4.1 Nano reads 1.0M tokens at once, Sonar 127k.
only GPT-4.1 Nano offers tool calls, structured output.
GPT-4.1 Nano was released about 3 months later.
Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).
| Specification | GPT-4.1 Nano | Sonar |
|---|---|---|
| Input price / 1M tokens | $0.10 | $1.00 |
| Output price / 1M tokens | $0.40 | $1.00 |
| Blended (3 in : 1 out) | $0.18 | $1.00 |
| Cached input / 1M | $0.03 | - |
| Context window | 1.0M | 127K |
| Max output | 943K | 114K |
| Input | image, text, file | text, image |
| Output | text | text |
| Tool calls | ||
| Structured output | ||
| Reasoning | ||
| Open weights | ||
| Intelligence index | 8 | 8 |
| Coding index | 11 | - |
| Agentic index | - | - |
| Released | Apr 14, 2025 | Jan 27, 2025 |
| Available on this deployment |
List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.
| Workload | GPT-4.1 Nano | Sonar | Difference |
|---|---|---|---|
| Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations. | $4.00 | $25.00 | $21.00 less on GPT-4.1 Nano |
| Document summaries100M in, 5M out - long inputs, short answers. | $12.00 | $105 | $93.00 less on GPT-4.1 Nano |
| Coding assistant60M in, 20M out - a team's editor assistant, output-heavy. | $14.00 | $80.00 | $66.00 less on GPT-4.1 Nano |
The two measure the same on the intelligence index, so the router treats them as peers and lets price, observed latency and your outcomes decide: GPT-4.1 Nano wins on cost, and a few bad outcomes on either move the next requests to the other.
# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
- { id: gpt-4.1-nano, kind: llm, metadata: { model: openai/gpt-4.1-nano } }
- { id: sonar, kind: llm, metadata: { model: perplexity/sonar } }
# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
- name: simple-requests-stay-cheap
when: { max_complexity: 0.45 }
prefer: [gpt-4.1-nano]
weight: 0.8
- name: hard-requests-escalate
when: { min_complexity: 0.45 }
prefer: [sonar]
weight: 0.8Every OpenAI and Perplexity model, with prices, is on the vendor pages; the rankings show what the router actually picks.