Pareto Code Router
5209°
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openrouter | 2,000,000 token context | $-1,000,000.00/M input, $-1,000,000.00/M output. The Pareto Router maintains a tiered shortlist of strong coding models, ranked by Artificial AnalysisOpens in new tab coding percentiles. Set min_coding_score between 0 and 1 on the pareto-router pluginOpens in new tab to control how strong a coder you need; higher scores select stronger (and typically more expensive) models. If you omit min_coding_score, the router defaults to the High tier. Selecting Nitro from the variant dropdown ranks the models in your tier by measured throughput and routes each request to the fastest one, so you trade some model variety for lower latency. Read the Pareto Router docsOpens in new tab for the full selection logic, fallback behavior, and how to customize routing. For another way to route, see the Auto Router.
Guides for this model
Open weights vs open source vs API-only: what you are actually allowed to do
The 10 cheapest ChatGPT alternatives in 2026: free local models, free tiers and flat-rate plans
Captain's notes
Notes from 2026-10-13
Pareto Code Router is an OpenRouter meta-router that automatically selects from a ranked shortlist of coding-focused models based on a score threshold you set. Rather than picking a single model, it delegates each request to whichever model in your chosen tier fits your quality or speed preference. It suits developers who want strong code generation without manually tracking which underlying model is currently best.
Known for
- Routes to top-ranked coding models based on Artificial Analysis coding percentiles
- Adjustable min_coding_score parameter lets you trade cost against coding strength
- Nitro variant prioritises measured throughput, reducing latency at the cost of model variety
- Defaults to a High coding tier if you send no score parameter
Watch out for
- Pricing is not published; actual cost depends entirely on whichever underlying model handles your request.
- Not open weights and cannot run locally; requires an OpenRouter account and API access.
- You are routing to other models, not a model itself — behaviour and output style will vary between requests.
Best for
Prompts to try
Refactor for readability
Refactor the following Python function so it is easier to read and maintain. Add type hints, rename any unclear variables, and split it into smaller helpers if that helps. Explain each change you made in a short comment above the relevant line.
def proc(d, x, flag=False):
r = []
for i in d:
if flag and i > x: r.append(i * 2)
elif not flag and i < x: r.append(i)
return r
Debug this async code
The following async Python snippet raises a RuntimeError about the event loop when run from a script. Identify the bug, explain why it happens, and provide a corrected version that works from a standard Python entry point.
import asyncio
async def fetch(): return 42
result = asyncio.get_event_loop().run_until_complete(fetch())
print(result)
asyncio.run(fetch())
Write a REST endpoint
Write a minimal FastAPI endpoint that accepts a POST request to /summarize with a JSON body containing a text field (string, max 5000 characters). Validate the input, return a 422 with a clear message if validation fails, and for now return the first 200 characters of the text as the summary field in the response JSON.
Compare with
- DeepSeek V4.1 FlashOpen-weights model1,048,576 token context · $0.04/M input, $0.68/M output
- GLM 5.3 FlashOpen-weights model1,048,576 token context · $0.02/M input, $0.72/M output
- Hy4 previewOpen-weights model1,048,576 token context · $0.83/M input, $2.50/M output
- MiMo-V2.6-FlashOpen-weights model1,050,000 token context · $0.14/M input, $0.28/M output
More text models from openrouter
Questions people ask
- Can I run Pareto Code Router locally or download its weights?
- No. It is an API-only meta-router on OpenRouter with no open weights and no Hugging Face repository.
- What does it actually cost per token?
- OpenRouter has not published a fixed price for this router; you pay whatever the selected underlying model charges, which varies by tier and request.
- How is this different from OpenRouter's Auto Router?
- Pareto Code Router restricts its pool to models ranked highly for coding specifically, and lets you tune the quality floor with min_coding_score; the Auto Router is a general-purpose selector across all tasks.
Captain's verdictA practical hands-off option if you want competitive code generation without babysitting model rankings, provided you can live with variable costs and no transparency into which model ran.
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
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Paste it into your Hugging Face card or Civitai description.
How this score adds up
This model has no popularity data from any source yet, so it carries a stand-in number below 7,000° that keeps the lists complete. It never ranks above a model with data. The breakdown appears here as soon as a source reports it.
Glossary: the terms used here
- Heat score
- One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
- Floor
- The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
- Download-equivalents
- Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
- Log scale
- Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
- Likes
- Thumbs up and likes from every source, worth half a download each on the log scale.
- Adoption rate
- How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
- Measured and estimated
- Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
- Seeder
- Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
- AI Horde
- A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
- Generation sites
- Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
- OpenRouter tokens
- A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
- Full model (checkpoint)
- The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
- LoRA and embedding
- Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
- Family and weights
- The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
- Age
- Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
- Family boost
- A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
- Stand-in score
- A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
- New! (grace period)
- A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
- Trend
- How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
- Typical model
- The middle of the catalog: half the models with a figure grew faster over the period, half slower.
Pareto Code Router is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models and check its heat score to see how it is trending.
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