Which LLM is the cheapest for our workload?

The best-for pages rank the live catalogue per task by the index that measures it, and the router picks the cheapest model that meets your quality rule for each request.

How much can we save on our LLM bill?

On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.

How often do model prices change?

The catalogue is refreshed from the vendors' price lists; each model page shows the date of its data.

90 days of the enterprise, pro and team plans free, no card needed. See the plans

OpenSmartRoute

Frontier reasoning model (llm-frontier) - OpenSmartRoute

All models

llm

Frontier reasoning model

llm-frontier · runs as GLM 4.7 Flash Z.ai via ollama-glm-4-7-flash

Most capable model for hard multi-step reasoning, math proofs, architecture design.

Answers requests here Personal data blocked by policy Tool calling

Try in playground JSON

Price per 1M tokens: $0.15; the target's declared price; the vendor's list price is below
Requests · 30d: 205; 10x+
Measured latency: 4.2 min; mean time to a complete answer over 30 days here · declared 34 min
Success rate: 97.1%; of the requests it answered; the quality prior is 93% (the router's starting estimate, not a benchmark)

Underlying model

Catalogue entry

Published by the vendor; the platform bills at the target's declared price.

GLM 4.7 Flash

reasoning open weights tools

Traffic over 30 days

Requests per day this target answered on this deployment, with the cost line.

requests (peak 41)
failed
cost

Tokens: 233.7K
Spend: $0.07
Previous window: 3 req

Routed for

Domains the signal layer detected on requests that ended here.

Creative69 · 49%

Capabilities

DomainsGeneral, Math, Coding, Legal, Medical, Finance, Data Analysis

ActionsReasoning, Planning, Code Generation, Code Review, Generation

Complexity band0.50 - 1.00

Languages*

Context window200K tokens

Streamingyes

Policy constraints

Hard stops enforced before scoring.

Data boundaryPublic

Regionsanywhere

PIInot allowed

Max input tokensunlimited

Tenantsall

Call it

Pin this target with model="llm-frontier", or send a candidate list and let the router choose and fall back.

curlbash

curl https://api.opensmartroute.ai/v1/chat/completions \
  -H "Authorization: Bearer $OSR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "llm-frontier", "messages": [{"role": "user", "content": "Prove that the square root of two is irrational, step by step."}]}'

OpenAI SDKpython

from openai import OpenAI

client = OpenAI(base_url="https://api.opensmartroute.ai/v1", api_key="osr_live_...")
resp = client.chat.completions.create(
    model="llm-frontier",            # pin this target, or "auto" to let the router choose
    messages=[{"role": "user", "content": "Prove that the square root of two is irrational, step by step."}],
    extra_body={"models": ["llm-frontier", "auto"]},   # fall back to the router's pick if it fails
)
print(resp.model, resp.choices[0].message.content)

One target among many